L144semantic compression

The candidates are:
  - theory: theory1, square, 5 and -5
  - entry: theory2, 8 and 59
  - entry: theory2, 12 and 139
  - entry: theory2, 4 and 11
  - theory: theory2, table, 0 and 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 and 5
  - entry: theory2, 7 and 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 and 31
  - theory1 theory size 2
  - theory: theory0, square, 4 and -7
The data are:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

Los candidatos son:
  - la teoría: theory1, square, 5 y -5
  - la entrada: theory2, 8 y 59
  - la entrada: theory2, 12 y 139
  - la entrada: theory2, 4 y 11
  - la teoría: theory2, mesa, 0 y 0
  - theory3 el tamaño de la teoría 3
  - la teoría: theory3, linear, 5 y 5
  - la entrada: theory2, 7 y 44
  - theory2 el tamaño de la teoría 10
  - theory0 el tamaño de la teoría 2
  - la entrada: theory2, 6 y 31
  - theory1 el tamaño de la teoría 2
  - la teoría: theory0, square, 4 y -7
Los datos son:
  - 8 la observación 59
  - 4 la observación 11
  - 6 la observación 31
  - 7 la observación 44
  - 12 la observación 139
Las reglas son:
  - la regla: a la teoría es lossless si y sólo si it predice every observation exactamente
  - la regla: choose el lossless la teoría de least tamaño
La semántica es: linear la forma y = p1 * x + p2; square la forma y = x * x + p2; constant la forma y = p2; la mesa la forma y = entry(x).
¿Qué smallest lossless la teoría?

候选项如下：
  - 的理论是：theory1、square、5和-5
  - 的条目是：theory2、8和59
  - 的条目是：theory2、12和139
  - 的条目是：theory2、4和11
  - 的理论是：theory2、桌子、0和0
  - theory3的理论规模是3
  - 的理论是：theory3、linear、5和5
  - 的条目是：theory2、7和44
  - theory2的理论规模是10
  - theory0的理论规模是2
  - 的条目是：theory2、6和31
  - theory1的理论规模是2
  - 的理论是：theory0、square、4和-7
数据如下：
  - 8观察到59
  - 4观察到11
  - 6观察到31
  - 7观察到44
  - 12观察到139
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

Adaylar:
  - kuram: theory1, square, 5 ve -5
  - entry: theory2, 8 ve 59
  - entry: theory2, 12 ve 139
  - entry: theory2, 4 ve 11
  - kuram: theory2, masa, 0 ve 0
  - theory3 3 kuram boyut
  - kuram: theory3, linear, 5 ve 5
  - entry: theory2, 7 ve 44
  - theory2 10 kuram boyut
  - theory0 2 kuram boyut
  - entry: theory2, 6 ve 31
  - theory1 2 kuram boyut
  - kuram: theory0, square, 4 ve -7
Veriler:
  - 8 59 obs
  - 4 11 obs
  - 6 31 obs
  - 7 44 obs
  - 12 139 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

Wagombea ni:
  - theory: theory1, square, 5 na -5
  - entry: theory2, 8 na 59
  - entry: theory2, 12 na 139
  - entry: theory2, 4 na 11
  - theory: theory2, meza, 0 na 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 na 5
  - entry: theory2, 7 na 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 na 31
  - theory1 theory size 2
  - theory: theory0, square, 4 na -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

The candidates are:
  - theory: theory1, square, 5 and -5
  - entry: theory2, 8 and 59
  - entry: theory2, 12 and 139
  - entry: theory2, 4 and 11
  - theory: theory2, table, 0 and 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 and 5
  - entry: theory2, 7 and 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 and 31
  - theory1 theory size 2
  - theory: theory0, square, 4 and -7
The data are:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

{candidates: [(theory theory1 square 5 -5) (entry theory2 8 59) (entry theory2 12 139) (entry theory2 4 11) (theory theory2 table 0 0) (theory_size theory3 3) (theory theory3 linear 5 5) (entry theory2 7 44) (theory_size theory2 10) (theory_size theory0 2) (entry theory2 6 31) (theory_size theory1 2) (theory theory0 square 4 -7)], data: [(obs 8 59) (obs 4 11) (obs 6 31) (obs 7 44) (obs 12 139)], query: smallest_lossless_theory, rules: [(rule (a_theory_is_lossless_iff_it_predicts_every_observation_exactly)) (rule (choose_the_lossless_theory_of_least_size))], semantics: [(form linear "y = p1 * x + p2") (form square "y = x * x + p2") (form constant "y = p2") (form table "y = entry(x)")]}

Die Kandidaten sind:
  - Theorie: theory1, square, 5 und -5
  - Eintrag: theory2, 8 und 59
  - Eintrag: theory2, 12 und 139
  - Eintrag: theory2, 4 und 11
  - Theorie: theory2, Tisch, 0 und 0
  - theory3 Theorie Größe 3
  - Theorie: theory3, linear, 5 und 5
  - Eintrag: theory2, 7 und 44
  - theory2 Theorie Größe 10
  - theory0 Theorie Größe 2
  - Eintrag: theory2, 6 und 31
  - theory1 Theorie Größe 2
  - Theorie: theory0, square, 4 und -7
Die Daten sind:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Die Regeln sind:
  - Regel ein Theorie werden verlustfrei gdw. er vorhersagen jeder Beobachtung genau
  - Regel wählen der verlustfrei Theorie aus geringst Größe
Die Semantik ist: linear formen y = p1 * x + p2; square formen y = x * x + p2; constant formen y = p2; der Tisch formen y = entry(x).
Was smallest verlustfrei Theorie?

Кандѝда̄т:
  - тѐо̄рија: theory1, square, 5 и -5
  - одредница: theory2, 8 и 59
  - одредница: theory2, 12 и 139
  - одредница: theory2, 4 и 11
  - тѐо̄рија: theory2, сто̑л, 0 и 0
  - theory3 тѐо̄рија величѝна 3
  - тѐо̄рија: theory3, linear, 5 и 5
  - одредница: theory2, 7 и 44
  - theory2 тѐо̄рија величѝна 10
  - theory0 тѐо̄рија величѝна 2
  - одредница: theory2, 6 и 31
  - theory1 тѐо̄рија величѝна 2
  - тѐо̄рија: theory0, square, 4 и -7
Податци:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Пра̏вило:
  - пра̏вило тѐо̄рија би̏ти lossless iff оно predvidjeti сва̏кӣ опа́жа̄ње тачно
  - пра̏вило изабрати lossless тѐо̄рија od minimalan величѝна
Сема̀нтика: linear oblik y = p1 * x + p2; square oblik y = x * x + p2; constant oblik y = p2; сто̑л oblik y = entry(x).
Smallest lossless тѐо̄рија kakav?

Ehdokkaat:
  - teoria: theory1, square, 5 ja -5
  - artikkeli: theory2, 8 ja 59
  - artikkeli: theory2, 12 ja 139
  - artikkeli: theory2, 4 ja 11
  - teoria: theory2, pöytä, 0 ja 0
  - theory3 teoria koko 3
  - teoria: theory3, linear, 5 ja 5
  - artikkeli: theory2, 7 ja 44
  - theory2 teoria koko 10
  - theory0 teoria koko 2
  - artikkeli: theory2, 6 ja 31
  - theory1 teoria koko 2
  - teoria: theory0, square, 4 ja -7
Tieto:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Säännöt:
  - sääntö teoria tulla häviötön joss se ennakoida jokainen havainnointi täsmälleen
  - sääntö valita häviötön teoria vaille vähin koko
Semantiikka: linear muotoilla y = p1 * x + p2; square muotoilla y = x * x + p2; constant muotoilla y = p2; pöytä muotoilla y = entry(x).
Mikä smallest häviötön teoria?

候选项如下：
  - 的理论是：theory1、square、5和-5
  - 的条目是：theory2、8和59
  - 的条目是：theory2、12和139
  - 的条目是：theory2、4和11
  - 的理论是：theory2、桌子、0和0
  - theory3的理论规模是3
  - 的理论是：theory3、linear、5和5
  - 的条目是：theory2、7和44
  - theory2的理论规模是10
  - theory0的理论规模是2
  - 的条目是：theory2、6和31
  - theory1的理论规模是2
  - 的理论是：theory0、square、4和-7
数据如下：
  - 8观察到59
  - 4观察到11
  - 6观察到31
  - 7观察到44
  - 12观察到139
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

候補者:
  - 理論:theory1, square, 5と-5
  - 項目:theory2, 8と59
  - 項目:theory2, 12と139
  - 項目:theory2, 4と11
  - 理論:theory2, 台, 0と0
  - theory33理論大きさ
  - 理論:theory3, linear, 5と5
  - 項目:theory2, 7と44
  - theory210理論大きさ
  - theory02理論大きさ
  - 項目:theory2, 6と31
  - theory12理論大きさ
  - 理論:theory0, square, 4と-7
資料:
  - 859obs
  - 411obs
  - 631obs
  - 744obs
  - 12139obs
規則:規則:理論れるロスレスiffこれ予言する凡ゆる観察正確に; 規則:選ぶロスレス理論の中の最小の大きさ.
意味論:lineary = p1 * x + p2形作る; squarey = x * x + p2形作る; constanty = p2形作る; 台y = entry(x)形作る.
smallestロスレス理論何と?

Adaylar:
  - kuram: theory1, square, 5 ve -5
  - entry: theory2, 8 ve 59
  - entry: theory2, 12 ve 139
  - entry: theory2, 4 ve 11
  - kuram: theory2, masa, 0 ve 0
  - theory3 3 kuram boyut
  - kuram: theory3, linear, 5 ve 5
  - entry: theory2, 7 ve 44
  - theory2 10 kuram boyut
  - theory0 2 kuram boyut
  - entry: theory2, 6 ve 31
  - theory1 2 kuram boyut
  - kuram: theory0, square, 4 ve -7
Veriler:
  - 8 59 obs
  - 4 11 obs
  - 6 31 obs
  - 7 44 obs
  - 12 139 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

مُرَشَّح:
  - نَظَرِيَّة: theory1، square، 5 وَـ -5
  - مَدْخَل: theory2، 8 وَـ 59
  - مَدْخَل: theory2، 12 وَـ 139
  - مَدْخَل: theory2، 4 وَـ 11
  - نَظَرِيَّة: theory2، طَاوِلَة، 0 وَـ 0
  - نَظَرِيَّة مَقَاس theory3 3
  - نَظَرِيَّة: theory3، linear، 5 وَـ 5
  - مَدْخَل: theory2، 7 وَـ 44
  - نَظَرِيَّة مَقَاس theory2 10
  - نَظَرِيَّة مَقَاس theory0 2
  - مَدْخَل: theory2، 6 وَـ 31
  - نَظَرِيَّة مَقَاس theory1 2
  - نَظَرِيَّة: theory0، square، 4 وَـ -7
بَيَانَات:
  - obs 8 59
  - obs 4 11
  - obs 6 31
  - obs 7 44
  - obs 12 139
قَانُون:
  - قَانُون نَظَرِيَّة كَانَ lossless iff هُوَ تَنَبَّأَ كُلّ رَصْد بِالضَّبْط
  - قَانُون اِخْتَارَ الـ lossless نَظَرِيَّة مِنْ أَقَلَّ مَقَاس
عِلْم اَلْمَعَانِي: شَكَّلَ linear y = p1 * x + p2؛ شَكَّلَ square y = x * x + p2؛ شَكَّلَ constant y = p2؛ شَكَّلَ الـ طَاوِلَة y = entry(x).
smallest lossless نَظَرِيَّة مَاذَا؟

Კანდიდატები:
  - თეორია: theory1, square, 5 და -5
  - სასათაურო სიტყვა: theory2, 8 და 59
  - სასათაურო სიტყვა: theory2, 12 და 139
  - სასათაურო სიტყვა: theory2, 4 და 11
  - თეორია: theory2, მაგიდა, 0 და 0
  - theory3 3 თეორია ზომა
  - თეორია: theory3, linear, 5 და 5
  - სასათაურო სიტყვა: theory2, 7 და 44
  - theory2 10 თეორია ზომა
  - theory0 2 თეორია ზომა
  - სასათაურო სიტყვა: theory2, 6 და 31
  - theory1 2 თეორია ზომა
  - თეორია: theory0, square, 4 და -7
Მონაცემები:
  - 8 59 obs
  - 4 11 obs
  - 6 31 obs
  - 7 44 obs
  - 12 139 obs
Წესი:
  - წესი თეორია ყოფნა უდანაკარგო iff ის predict ყველა დაკვირვება ზუსტად
  - წესი ამორჩევა უდანაკარგო თეორია of least ზომა
Სემანტიკა: linear y = p1 * x + p2 ბლანკი; square y = x * x + p2 ბლანკი; constant y = p2 ბლანკი; მაგიდა y = entry(x) ბლანკი.
Smallest უდანაკარგო თეორია რა?

Kaiwhakauru:
  - ariā: theory1, square, 5 me -5
  - tāurunga: theory2, 8 me 59
  - tāurunga: theory2, 12 me 139
  - tāurunga: theory2, 4 me 11
  - ariā: theory2, tēpu, 0 me 0
  - ariā size theory3 3
  - ariā: theory3, linear, 5 me 5
  - tāurunga: theory2, 7 me 44
  - ariā size theory2 10
  - ariā size theory0 2
  - tāurunga: theory2, 6 me 31
  - ariā size theory1 2
  - ariā: theory0, square, 4 me -7
Hōtuku:
  - obs 8 59
  - obs 4 11
  - obs 6 31
  - obs 7 44
  - obs 12 139
Rekureihana:
  - rekureihana ariā is lossless iff it matakite every observation pū
  - rekureihana whiri te lossless ariā o least size
Semantics: āhua linear y = p1 * x + p2; āhua square y = x * x + p2; āhua constant y = p2; āhua te tēpu y = entry(x).
Smallest lossless ariā unutai?

Candidates:
  - lý thuyết: theory1, square, 5 và -5
  - mục từ: theory2, 8 và 59
  - mục từ: theory2, 12 và 139
  - mục từ: theory2, 4 và 11
  - lý thuyết: theory2, bàn, 0 và 0
  - theory3 lý thuyết kích thước 3
  - lý thuyết: theory3, linear, 5 và 5
  - mục từ: theory2, 7 và 44
  - theory2 lý thuyết kích thước 10
  - theory0 lý thuyết kích thước 2
  - mục từ: theory2, 6 và 31
  - theory1 lý thuyết kích thước 2
  - lý thuyết: theory0, square, 4 và -7
Dữ liệu:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Quy tắc:
  - quy tắc lý thuyết được lossless iff nó dự báo mỗi observation đúng rồi
  - quy tắc chọn the lossless lý thuyết bằng least kích thước
Ngữ nghĩa: linear làm thành y = p1 * x + p2; square làm thành y = x * x + p2; constant làm thành y = p2; bàn làm thành y = entry(x).
Smallest lossless lý thuyết gì?

ผู้สมัคร:
  - ทฤษฎี:theory1, square, 5และ-5
  - entry:theory2, 8และ59
  - entry:theory2, 12และ139
  - entry:theory2, 4และ11
  - ทฤษฎี:theory2, โต๊ะ, 0และ0
  - theory3ทฤษฎีขนาด3
  - ทฤษฎี:theory3, linear, 5และ5
  - entry:theory2, 7และ44
  - theory2ทฤษฎีขนาด10
  - theory0ทฤษฎีขนาด2
  - entry:theory2, 6และ31
  - theory1ทฤษฎีขนาด2
  - ทฤษฎี:theory0, square, 4และ-7
ข้อมูล:
  - 8obs59
  - 4obs11
  - 6obs31
  - 7obs44
  - 12obs139
กฎ:กฎ:ทฤษฎีถูกlosslessiffมันทำนายทุกการสังเกตexactly; กฎ:เลือกlosslessทฤษฎีของleastขนาด.
อรรถศาสตร์:linearรูปร่างy = p1 * x + p2; squareรูปร่างy = x * x + p2; constantรูปร่างy = p2; โต๊ะรูปร่างy = entry(x).
smallestlosslessทฤษฎีอะไร?

வேட்பாளர்:
  - theory: theory1, square, 5 மற்றும் -5
  - உள்நுழைவதற்கு அனுமதி: theory2, 8 மற்றும் 59
  - உள்நுழைவதற்கு அனுமதி: theory2, 12 மற்றும் 139
  - உள்நுழைவதற்கு அனுமதி: theory2, 4 மற்றும் 11
  - theory: theory2, மேசை, 0 மற்றும் 0
  - theory3 3 theory size
  - theory: theory3, linear, 5 மற்றும் 5
  - உள்நுழைவதற்கு அனுமதி: theory2, 7 மற்றும் 44
  - theory2 10 theory size
  - theory0 2 theory size
  - உள்நுழைவதற்கு அனுமதி: theory2, 6 மற்றும் 31
  - theory1 2 theory size
  - theory: theory0, square, 4 மற்றும் -7
தரவுகள்:
  - 8 59 obs
  - 4 11 obs
  - 6 31 obs
  - 7 44 obs
  - 12 139 obs
rules: rule theory படு lossless iff it கணி ஒவ்வொரு observation exactly; rule choose lossless theory கொண்ட least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; மேசை y = entry(x) form.
smallest lossless theory என்ன?

Wagombea ni:
  - theory: theory1, square, 5 na -5
  - entry: theory2, 8 na 59
  - entry: theory2, 12 na 139
  - entry: theory2, 4 na 11
  - theory: theory2, meza, 0 na 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 na 5
  - entry: theory2, 7 na 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 na 31
  - theory1 theory size 2
  - theory: theory0, square, 4 na -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

Candidates:
  - theory: theory1, square, 5 dóó -5
  - entry: theory2, 8 dóó 59
  - entry: theory2, 12 dóó 139
  - entry: theory2, 4 dóó 11
  - theory: theory2, bikááʼ adání, 0 dóó 0
  - theory3 3 theory size
  - theory: theory3, linear, 5 dóó 5
  - entry: theory2, 7 dóó 44
  - theory2 10 theory size
  - theory0 2 theory size
  - entry: theory2, 6 dóó 31
  - theory1 2 theory size
  - theory: theory0, square, 4 dóó -7
Data:
  - 8 59 obs
  - 4 11 obs
  - 6 31 obs
  - 7 44 obs
  - 12 139 obs
Bee hazʼáanii:
  - bee hazʼáanii theory átʼé lossless iff it predict every observation exactly
  - bee hazʼáanii choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; bikááʼ adání y = entry(x) form.
Smallest lossless theory haʼátʼíísh?

Candidates:
  - theory: theory1, square, 5 aamma -5
  - entry: theory2, 8 aamma 59
  - entry: theory2, 12 aamma 139
  - entry: theory2, 4 aamma 11
  - theory: theory2, table, 0 aamma 0
  - theory3 3 theory size
  - theory: theory3, linear, 5 aamma 5
  - entry: theory2, 7 aamma 44
  - theory2 10 theory size
  - theory0 2 theory size
  - entry: theory2, 6 aamma 31
  - theory1 2 theory size
  - theory: theory0, square, 4 aamma -7
Data:
  - 8 59 obs
  - 4 11 obs
  - 6 31 obs
  - 7 44 obs
  - 12 139 obs
Rules: rule theory a lossless iff una predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 blanketti; square y = x * x + p2 blanketti; constant y = p2 blanketti; table y = entry(x) blanketti.
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 5 na -5
  - entry: theory2, 8 na 59
  - entry: theory2, 12 na 139
  - entry: theory2, 4 na 11
  - theory: theory2, table, 0 na 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 na 5
  - entry: theory2, 7 na 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 na 31
  - theory1 theory size 2
  - theory: theory0, square, 4 na -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory bilong least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 5 -5
  - entry: theory2, 8 59
  - entry: theory2, 12 139
  - entry: theory2, 4 11
  - theory: theory2, table, 0 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 5
  - entry: theory2, 7 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 31
  - theory1 theory size 2
  - theory: theory0, square, 4 -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Nikanixi:
  - nikanixi theory is lossless iff it predict every observation exactly
  - nikanixi choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory kwèch?

Candidates:
  - theory: theory1, square, 5 а -5
  - entry: theory2, 8 а 59
  - entry: theory2, 12 а 139
  - entry: theory2, 4 а 11
  - theory: theory2, table, 0 а 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 а 5
  - entry: theory2, 7 а 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 а 31
  - theory1 theory size 2
  - theory: theory0, square, 4 а -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Rules:
  - rule theory хила lossless iff it predict дерриг observation exactly
  - rule хержа lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory фу?

후보자:
  - 이론: theory1, square, 5 -5
  - 항목: theory2, 8 59
  - 항목: theory2, 12 139
  - 항목: theory2, 4 11
  - 이론: theory2, 테이블, 0 0
  - theory3 3 이론 크기
  - 이론: theory3, linear, 5 5
  - 항목: theory2, 7 44
  - theory2 10 이론 크기
  - theory0 2 이론 크기
  - 항목: theory2, 6 31
  - theory1 2 이론 크기
  - 이론: theory0, square, 4 -7
자료:
  - 8 59 obs
  - 4 11 obs
  - 6 31 obs
  - 7 44 obs
  - 12 139 obs
규칙: 규칙 이론 is lossless iff 이것 예언하다 각 관찰 정확하게; 규칙 고르다 lossless 이론...의 가장 적게 크기.
의미론: linear y = p1 * x + p2 형상; square y = x * x + p2 형상; constant y = p2 형상; 테이블 y = entry(x) 형상.
smallest lossless 이론 무엇?

Kandidatu:
  - theory: theory1, square, 5 eta -5
  - sarrera: theory2, 8 eta 59
  - sarrera: theory2, 12 eta 139
  - sarrera: theory2, 4 eta 11
  - theory: theory2, mahai, 0 eta 0
  - theory3 3 theory tamaina
  - theory: theory3, linear, 5 eta 5
  - sarrera: theory2, 7 eta 44
  - theory2 10 theory tamaina
  - theory0 2 theory tamaina
  - sarrera: theory2, 6 eta 31
  - theory1 2 theory tamaina
  - theory: theory0, square, 4 eta -7
Data:
  - 8 59 obs
  - 4 11 obs
  - 6 31 obs
  - 7 44 obs
  - 12 139 obs
Arau:
  - arau bat theory izan lossless iff it aurresan every observation exactly
  - arau aukeratu the lossless theory of least tamaina
Semantics: linear y = p1 * x + p2 forma; square y = x * x + p2 forma; constant y = p2 forma; mahai y = entry(x) forma.
Smallest lossless theory zer?

ᎠᏙᎩᏯᏍᎩ:
  - theory: theory1, square, 5 ᎠᎴ -5
  - entry: theory2, 8 ᎠᎴ 59
  - entry: theory2, 12 ᎠᎴ 139
  - entry: theory2, 4 ᎠᎴ 11
  - theory: theory2, ᎦᏍᎩᎶ, 0 ᎠᎴ 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 ᎠᎴ 5
  - entry: theory2, 7 ᎠᎴ 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 ᎠᎴ 31
  - theory1 theory size 2
  - theory: theory0, square, 4 ᎠᎴ -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ᎦᏍᎩᎶ form y = entry(x).
What smallest lossless theory?

Candidates:
  - theory: theory1, square, 5 -5
  - entry: theory2, 8 59
  - entry: theory2, 12 139
  - entry: theory2, 4 11
  - theory: theory2, patacha, 0 0
  - theory3 theory chhika 3
  - theory: theory3, linear, 5 5
  - entry: theory2, 7 44
  - theory2 theory chhika 10
  - theory0 theory chhika 2
  - entry: theory2, 6 31
  - theory1 theory chhika 2
  - theory: theory0, square, 4 -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Rules:
  - rule theory tiyay lossless iff it predict tukuy observation exactly
  - rule akllay lossless theory of least chhika
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; patacha form y = entry(x).
Smallest lossless theory what?

Candidates:
  - тиориэ: theory1, square, 5 ыкӏи -5
  - entry: theory2, 8 ыкӏи 59
  - entry: theory2, 12 ыкӏи 139
  - entry: theory2, 4 ыкӏи 11
  - тиориэ: theory2, table, 0 ыкӏи 0
  - theory3 3 тиориэ size
  - тиориэ: theory3, linear, 5 ыкӏи 5
  - entry: theory2, 7 ыкӏи 44
  - theory2 10 тиориэ size
  - theory0 2 тиориэ size
  - entry: theory2, 6 ыкӏи 31
  - theory1 2 тиориэ size
  - тиориэ: theory0, square, 4 ыкӏи -7
Data:
  - 8 59 obs
  - 4 11 obs
  - 6 31 obs
  - 7 44 obs
  - 12 139 obs
Rules: rule тиориэ is lossless iff it predict every observation exactly; rule choose the lossless тиориэ of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless тиориэ сыд?

Candidates:
  - theory: theory1, square, 5 thiab -5
  - entry: theory2, 8 thiab 59
  - entry: theory2, 12 thiab 139
  - entry: theory2, 4 thiab 11
  - theory: theory2, rooj, 0 thiab 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 thiab 5
  - entry: theory2, 7 thiab 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 thiab 31
  - theory1 theory size 2
  - theory: theory0, square, 4 thiab -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Cai: cai theory is lossless iff nws predict every observation exactly; cai choose lossless theory of least size.
Lub ntsiab: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; rooj form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 5 -5
  - entry: theory2, 8 59
  - entry: theory2, 12 139
  - entry: theory2, 4 11
  - theory: theory2, table, 0 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 5
  - entry: theory2, 7 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 31
  - theory1 theory size 2
  - theory: theory0, square, 4 -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of wy krook size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory ining-jak?

Candidates:
  - theory: theory1, square, 5 micha' -5
  - entry: theory2, 8 micha' 59
  - entry: theory2, 12 micha' 139
  - entry: theory2, 4 micha' 11
  - theory: theory2, table, 0 micha' 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 micha' 5
  - entry: theory2, 7 micha' 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 micha' 31
  - theory1 theory size 2
  - theory: theory0, square, 4 micha' -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory nanta?

Candidates:
  - theory: theory1, square, 5 カ -5
  - entry: theory2, 8 カ 59
  - entry: theory2, 12 カ 139
  - entry: theory2, 4 カ 11
  - theory: theory2, table, 0 カ 0
  - theory3 3 theory size
  - theory: theory3, linear, 5 カ 5
  - entry: theory2, 7 カ 44
  - theory2 10 theory size
  - theory0 2 theory size
  - entry: theory2, 6 カ 31
  - theory1 2 theory size
  - theory: theory0, square, 4 カ -7
Data:
  - 8 59 obs
  - 4 11 obs
  - 6 31 obs
  - 7 44 obs
  - 12 139 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 ノカ; square y = x * x + p2 ノカ; constant y = p2 ノカ; table y = entry(x) ノカ.
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 5 ынкъам -5
  - entry: theory2, 8 ынкъам 59
  - entry: theory2, 12 ынкъам 139
  - entry: theory2, 4 ынкъам 11
  - theory: theory2, table, 0 ынкъам 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 ынкъам 5
  - entry: theory2, 7 ынкъам 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 ынкъам 31
  - theory1 theory size 2
  - theory: theory0, square, 4 ынкъам -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 5 yéetel -5
  - entry: theory2, 8 yéetel 59
  - entry: theory2, 12 yéetel 139
  - entry: theory2, 4 yéetel 11
  - theory: theory2, table, 0 yéetel 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 yéetel 5
  - entry: theory2, 7 yéetel 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 yéetel 31
  - theory1 theory size 2
  - theory: theory0, square, 4 yéetel -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Rules:
  - rule theory yan lossless iff it predict every observation exactly
  - rule yéey lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 5 -5
  - entry: theory2, 8 59
  - entry: theory2, 12 139
  - entry: theory2, 4 11
  - theory: theory2, mę́soną, 0 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 5
  - entry: theory2, 7 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 31
  - theory1 theory size 2
  - theory: theory0, square, 4 -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Rules:
  - rule theory is lossless iff ą́wąną predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mę́soną form y = entry(x).
Smallest lossless theory híli?

Candidates:
  - theory: theory1, square, 5 na -5
  - entry: theory2, 8 na 59
  - entry: theory2, 12 na 139
  - entry: theory2, 4 na 11
  - theory: theory2, table, 0 na 0
  - theory3 3 theory size
  - theory: theory3, linear, 5 na 5
  - entry: theory2, 7 na 44
  - theory2 10 theory size
  - theory0 2 theory size
  - entry: theory2, 6 na 31
  - theory1 2 theory size
  - theory: theory0, square, 4 na -7
Data:
  - 8 59 obs
  - 4 11 obs
  - 6 31 obs
  - 7 44 obs
  - 12 139 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 5 -5
  - entry: theory2, 8 59
  - entry: theory2, 12 139
  - entry: theory2, 4 11
  - theory: theory2, table, 0 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 5
  - entry: theory2, 7 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 31
  - theory1 theory size 2
  - theory: theory0, square, 4 -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 5 -5
  - entry: theory2, 8 59
  - entry: theory2, 12 139
  - entry: theory2, 4 11
  - theory: theory2, table, 0 0
  - theory3 3 theory size
  - theory: theory3, linear, 5 5
  - entry: theory2, 7 44
  - theory2 10 theory size
  - theory0 2 theory size
  - entry: theory2, 6 31
  - theory1 2 theory size
  - theory: theory0, square, 4 -7
Data:
  - 8 59 obs
  - 4 11 obs
  - 6 31 obs
  - 7 44 obs
  - 12 139 obs
Rules:
  - rule maya theory is lossless iff it predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 5 ǂʻá -5
  - entry: theory2, 8 ǂʻá 59
  - entry: theory2, 12 ǂʻá 139
  - entry: theory2, 4 ǂʻá 11
  - theory: theory2, table, 0 ǂʻá 0
  - theory3 theory ʻǁnàhã 3
  - theory: theory3, linear, 5 ǂʻá 5
  - entry: theory2, 7 ǂʻá 44
  - theory2 theory ʻǁnàhã 10
  - theory0 theory ʻǁnàhã 2
  - entry: theory2, 6 ǂʻá 31
  - theory1 theory ʻǁnàhã 2
  - theory: theory0, square, 4 ǂʻá -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Rules:
  - rule theory ǀîi lossless iff èh predict every observation exactly
  - rule choose lossless theory of least ʻǁnàhã
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 5 -5
  - entry: theory2, 8 59
  - entry: theory2, 12 139
  - entry: theory2, 4 11
  - theory: theory2, остол, 0 0
  - theory3 3 theory size
  - theory: theory3, linear, 5 5
  - entry: theory2, 7 44
  - theory2 10 theory size
  - theory0 2 theory size
  - entry: theory2, 6 31
  - theory1 2 theory size
  - theory: theory0, square, 4 -7
Data:
  - 8 59 obs
  - 4 11 obs
  - 6 31 obs
  - 7 44 obs
  - 12 139 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; остол y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 5 -5
  - entry: theory2, 8 59
  - entry: theory2, 12 139
  - entry: theory2, 4 11
  - theory: theory2, table, 0 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 5
  - entry: theory2, 7 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 31
  - theory1 theory size 2
  - theory: theory0, square, 4 -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 5 -5
  - entry: theory2, 8 59
  - entry: theory2, 12 139
  - entry: theory2, 4 11
  - theory: theory2, table, 0 0
  - theory3 3 theory size
  - theory: theory3, linear, 5 5
  - entry: theory2, 7 44
  - theory2 10 theory size
  - theory0 2 theory size
  - entry: theory2, 6 31
  - theory1 2 theory size
  - theory: theory0, square, 4 -7
Data:
  - 8 59 obs
  - 4 11 obs
  - 6 31 obs
  - 7 44 obs
  - 12 139 obs
Rules:
  - rule theory is lossless iff kitu predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 5 -5
  - entry: theory2, 8 59
  - entry: theory2, 12 139
  - entry: theory2, 4 11
  - theory: theory2, mesa, 0 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 5
  - entry: theory2, 7 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 31
  - theory1 theory size 2
  - theory: theory0, square, 4 -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mesa form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 5 -5
  - entry: theory2, 8 59
  - entry: theory2, 12 139
  - entry: theory2, 4 11
  - theory: theory2, table, 0 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 5
  - entry: theory2, 7 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 31
  - theory1 theory size 2
  - theory: theory0, square, 4 -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Rules:
  - rule theory nemi lossless iff yaja predict every observation exactly
  - rule choose ne lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ne table form y = entry(x).
Smallest lossless theory tay?

Les candidats sont:
  - théorie: theory1, square, 5 et -5
  - article: theory2, 8 et 59
  - article: theory2, 12 et 139
  - article: theory2, 4 et 11
  - théorie: theory2, table, 0 et 0
  - theory3 théorie taille 3
  - théorie: theory3, linear, 5 et 5
  - article: theory2, 7 et 44
  - theory2 théorie taille 10
  - theory0 théorie taille 2
  - article: theory2, 6 et 31
  - theory1 théorie taille 2
  - théorie: theory0, square, 4 et -7
Les données sont:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Les règles sont:
  - règle un théorie être lossless ssi il prédire tout observation exactement
  - règle choisir le lossless théorie du moindre taille
La sémantique est : linear former y = p1 * x + p2 ; square former y = x * x + p2 ; constant former y = p2 ; la table former y = entry(x).
Quoi smallest lossless théorie ?

Kandidato:
  - teorio: theory1, square, 5 kaj -5
  - entry: theory2, 8 kaj 59
  - entry: theory2, 12 kaj 139
  - entry: theory2, 4 kaj 11
  - teorio: theory2, tablo, 0 kaj 0
  - theory3 teorio grandeco 3
  - teorio: theory3, linear, 5 kaj 5
  - entry: theory2, 7 kaj 44
  - theory2 teorio grandeco 10
  - theory0 teorio grandeco 2
  - entry: theory2, 6 kaj 31
  - theory1 teorio grandeco 2
  - teorio: theory0, square, 4 kaj -7
Datumo:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Regulo: regulo teorio egali lossless iff ĝi predict ĉiu observo ekzakte; regulo elekti lossless teorio de plej malmulta grandeco.
Semantics: linear formi y = p1 * x + p2; square formi y = x * x + p2; constant formi y = p2; tablo formi y = entry(x).
Smallest lossless teorio kio?

Indulók:
  - elmélet: theory1, square, 5 és -5
  - szócikk: theory2, 8 és 59
  - szócikk: theory2, 12 és 139
  - szócikk: theory2, 4 és 11
  - elmélet: theory2, asztal, 0 és 0
  - theory3 elmélet méret 3
  - elmélet: theory3, linear, 5 és 5
  - szócikk: theory2, 7 és 44
  - theory2 elmélet méret 10
  - theory0 elmélet méret 2
  - szócikk: theory2, 6 és 31
  - theory1 elmélet méret 2
  - elmélet: theory0, square, 4 és -7
Adat:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Szabályok:
  - szabály elmélet van veszteségmentes acsa az megjósol minden megfigyelés pontosan
  - szabály kiválaszt a veszteségmentes elmélet of legkisebb méret
Szemantika: linear kialakít y = p1 * x + p2; square kialakít y = x * x + p2; constant kialakít y = p2; a asztal kialakít y = entry(x).
Smallest veszteségmentes elmélet melyik?

候選人:
  - theory:theory1, square, 5及-5
  - entry:theory2, 8及59
  - entry:theory2, 12及139
  - entry:theory2, 4及11
  - theory:theory2, 檯, 0及0
  - theory3theory size3
  - theory:theory3, linear, 5及5
  - entry:theory2, 7及44
  - theory2theory size10
  - theory0theory size2
  - entry:theory2, 6及31
  - theory1theory size2
  - theory:theory0, square, 4及-7
數據:
  - 8obs59
  - 4obs11
  - 6obs31
  - 7obs44
  - 12obs139
rules:rule:一theory是losslessiffitpredict每observationexactly; rule:揀losslesstheory...嘅leastsize.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; 檯formy = entry(x).
smallest lossless theory乜嘢?

Candidates:
  - theory: theory1, square, 5 とぅ -5
  - entry: theory2, 8 とぅ 59
  - entry: theory2, 12 とぅ 139
  - entry: theory2, 4 とぅ 11
  - theory: theory2, table, 0 とぅ 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 とぅ 5
  - entry: theory2, 7 とぅ 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 とぅ 31
  - theory1 theory size 2
  - theory: theory0, square, 4 とぅ -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Rules: rule theory 有ん lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Үміткер:
  - теория: theory1, square, 5 және -5
  - entry: theory2, 8 және 59
  - entry: theory2, 12 және 139
  - entry: theory2, 4 және 11
  - теория: theory2, үстел, 0 және 0
  - theory3 теория мөлшер 3
  - теория: theory3, linear, 5 және 5
  - entry: theory2, 7 және 44
  - theory2 теория мөлшер 10
  - theory0 теория мөлшер 2
  - entry: theory2, 6 және 31
  - theory1 теория мөлшер 2
  - теория: theory0, square, 4 және -7
Деректер:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Ереже: ереже теория is lossless iff ол predict әр бақылау exactly; ереже таңдау lossless теория туралы least мөлшер.
Семантикалық: linear пішін y = p1 * x + p2; square пішін y = x * x + p2; constant пішін y = p2; үстел пішін y = entry(x).
Smallest lossless теория не?

מועמדת:
  - תּוֹרָה: theory1, square, 5 וְ־ -5
  - entry: theory2, 8 וְ־ 59
  - entry: theory2, 12 וְ־ 139
  - entry: theory2, 4 וְ־ 11
  - תּוֹרָה: theory2, טַבְלָה, 0 וְ־ 0
  - theory3 תּוֹרָה גֹּדֶל 3
  - תּוֹרָה: theory3, linear, 5 וְ־ 5
  - entry: theory2, 7 וְ־ 44
  - theory2 תּוֹרָה גֹּדֶל 10
  - theory0 תּוֹרָה גֹּדֶל 2
  - entry: theory2, 6 וְ־ 31
  - theory1 תּוֹרָה גֹּדֶל 2
  - תּוֹרָה: theory0, square, 4 וְ־ -7
נְתוּנִים:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
מָשַׁל:
  - מָשַׁל אַחַת תּוֹרָה הוא lossless אםם זֶה predict כֹּל תַּצְפִּית בדיוק
  - מָשַׁל בחר ה־ lossless תּוֹרָה שֶׁל least גֹּדֶל
תורת המשמעים: linear צורה y = p1 * x + p2; square צורה y = x * x + p2; constant צורה y = p2; טַבְלָה ה־ צורה y = entry(x).
איזה smallest lossless תּוֹרָה?

Candidates:
  - theory: theory1, square, 5 დო -5
  - entry: theory2, 8 დო 59
  - entry: theory2, 12 დო 139
  - entry: theory2, 4 დო 11
  - theory: theory2, table, 0 დო 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 დო 5
  - entry: theory2, 7 დო 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 დო 31
  - theory1 theory size 2
  - theory: theory0, square, 4 დო -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Kandidat:
  - teori: theory1, square, 5 dan -5
  - lema: theory2, 8 dan 59
  - lema: theory2, 12 dan 139
  - lema: theory2, 4 dan 11
  - teori: theory2, meja, 0 dan 0
  - theory3 teori ukuran 3
  - teori: theory3, linear, 5 dan 5
  - lema: theory2, 7 dan 44
  - theory2 teori ukuran 10
  - theory0 teori ukuran 2
  - lema: theory2, 6 dan 31
  - theory1 teori ukuran 2
  - teori: theory0, square, 4 dan -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Rules:
  - rule teori berada lossless iff it predict setiap observation tepat
  - rule memilih si lossless teori dari least ukuran
Semantik: linear formulir y = p1 * x + p2; square formulir y = x * x + p2; constant formulir y = p2; meja si formulir y = entry(x).
Smallest lossless teori apa?

បេក្ខជន:
  - ទ្រឹស្ដី:theory1, square, 5នឹង-5
  - មេពាក្យ:theory2, 8នឹង59
  - មេពាក្យ:theory2, 12នឹង139
  - មេពាក្យ:theory2, 4នឹង11
  - ទ្រឹស្ដី:theory2, តុ, 0នឹង0
  - theory3ទ្រឹស្ដីទំហំ3
  - ទ្រឹស្ដី:theory3, linear, 5នឹង5
  - មេពាក្យ:theory2, 7នឹង44
  - theory2ទ្រឹស្ដីទំហំ10
  - theory0ទ្រឹស្ដីទំហំ2
  - មេពាក្យ:theory2, 6នឹង31
  - theory1ទ្រឹស្ដីទំហំ2
  - ទ្រឹស្ដី:theory0, square, 4នឹង-7
ទិន្នន័យ:
  - 8obs59
  - 4obs11
  - 6obs31
  - 7obs44
  - 12obs139
ក្បួន:ក្បួន:ទ្រឹស្ដីត្រូវបានlosslessiffវាចាប់យាមរាល់គំនន់exactly; ក្បួន:រើសthelosslessទ្រឹស្ដីនៃleastទំហំ.
និឃណ្ដសាស្ត្រ:linearគ្រោងy = p1 * x + p2; squareគ្រោងy = x * x + p2; constantគ្រោងy = p2; តុគ្រោងy = entry(x).
smallestlosslessទ្រឹស្ដីអី?

ຜູ້ສະໝັກ:
  - ທິດສະດີ:theory1, square, 5ແລະ-5
  - entry:theory2, 8ແລະ59
  - entry:theory2, 12ແລະ139
  - entry:theory2, 4ແລະ11
  - ທິດສະດີ:theory2, ໂຕະ, 0ແລະ0
  - theory3ທິດສະດີຂະຫນາດ3
  - ທິດສະດີ:theory3, linear, 5ແລະ5
  - entry:theory2, 7ແລະ44
  - theory2ທິດສະດີຂະຫນາດ10
  - theory0ທິດສະດີຂະຫນາດ2
  - entry:theory2, 6ແລະ31
  - theory1ທິດສະດີຂະຫນາດ2
  - ທິດສະດີ:theory0, square, 4ແລະ-7
ຂໍ້ມູນ:
  - 8obs59
  - 4obs11
  - 6obs31
  - 7obs44
  - 12obs139
ກະຕິກາ:ກະຕິກາ:ທິດສະດີຢູ່losslessiffມັນທຳນວາຍທຸກobservationexactly; ກະຕິກາ:ເລືອກlosslessທິດສະດີຂອງleastຂະຫນາດ.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; ໂຕະformy = entry(x).
smallestlosslessທິດສະດີຫຍັງ?

candidates:
  - theory: theory1, square, 5 మరియు -5
  - entry: theory2, 8 మరియు 59
  - entry: theory2, 12 మరియు 139
  - entry: theory2, 4 మరియు 11
  - theory: theory2, బల్ల, 0 మరియు 0
  - theory3 3 theory size
  - theory: theory3, linear, 5 మరియు 5
  - entry: theory2, 7 మరియు 44
  - theory2 10 theory size
  - theory0 2 theory size
  - entry: theory2, 6 మరియు 31
  - theory1 2 theory size
  - theory: theory0, square, 4 మరియు -7
data:
  - 8 59 obs
  - 4 11 obs
  - 6 31 obs
  - 7 44 obs
  - 12 139 obs
నియమం: నియమం theory ఉండు lossless iff it predict ప్రతి పరిశీలన exactly; నియమం choose lossless theory of least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; బల్ల y = entry(x) form.
smallest lossless theory ఏమిటి?

Candidates:
  - theory: theory1, square, 5 -5
  - entry: theory2, 8 59
  - entry: theory2, 12 139
  - entry: theory2, 4 11
  - theory: theory2, table, 0 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 5
  - entry: theory2, 7 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 31
  - theory1 theory size 2
  - theory: theory0, square, 4 -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Rules: rule theory wà lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
What smallest lossless theory?

Candidates:
  - theory: theory1, square, 5 -5
  - entry: theory2, 8 59
  - entry: theory2, 12 139
  - entry: theory2, 4 11
  - theory: theory2, table, 0 0
  - theory3 3 theory size
  - theory: theory3, linear, 5 5
  - entry: theory2, 7 44
  - theory2 10 theory size
  - theory0 2 theory size
  - entry: theory2, 6 31
  - theory1 2 theory size
  - theory: theory0, square, 4 -7
Data:
  - 8 59 obs
  - 4 11 obs
  - 6 31 obs
  - 7 44 obs
  - 12 139 obs
Rules:
  - rule theory naiágúóli lossless iff it predict every observation exactly
  - rule choose the lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

candidates:
  - theory: theory1, square, 5 -5
  - entry: theory2, 8 59
  - entry: theory2, 12 139
  - entry: theory2, 4 11
  - theory: theory2, table, 0 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 5
  - entry: theory2, 7 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 31
  - theory1 theory size 2
  - theory: theory0, square, 4 -7
data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
smallest lossless theory what?

Candidates:
  - theory: theory1, square, 5 -5
  - entry: theory2, 8 59
  - entry: theory2, 12 139
  - entry: theory2, 4 11
  - theory: theory2, tafra, 0 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 5
  - entry: theory2, 7 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 31
  - theory1 theory size 2
  - theory: theory0, square, 4 -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; tafra form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 5 -5
  - entry: theory2, 8 59
  - entry: theory2, 12 139
  - entry: theory2, 4 11
  - theory: theory2, táxemésėhestȯtse, 0 0
  - theory3 theory size 3
  - theory: theory3, linear, 5 5
  - entry: theory2, 7 44
  - theory2 theory size 10
  - theory0 theory size 2
  - entry: theory2, 6 31
  - theory1 theory size 2
  - theory: theory0, square, 4 -7
Data:
  - 8 obs 59
  - 4 obs 11
  - 6 obs 31
  - 7 obs 44
  - 12 obs 139
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; táxemésėhestȯtse form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 5 -5
  - entry: theory2, 8 59
  - entry: theory2, 12 139
  - entry: theory2, 4 11
  - theory: theory2, ствал, 0 0
  - theory3 3 theory size
  - theory: theory3, linear, 5 5
  - entry: theory2, 7 44
  - theory2 10 theory size
  - theory0 2 theory size
  - entry: theory2, 6 31
  - theory1 2 theory size
  - theory: theory0, square, 4 -7
Data:
  - 8 59 obs
  - 4 11 obs
  - 6 31 obs
  - 7 44 obs
  - 12 139 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; ствал y = entry(x) form.
Smallest lossless theory вуч?

The candidates are:
  - theory: theory1, square, 7 and 6
  - entry: theory3, 7 and 38
  - entry: theory3, 4 and 20
  - entry: theory3, 9 and 50
  - theory3 theory size 10
  - theory: theory3, table, 0 and 0
  - theory: theory2, linear, 6 and -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 and 2
  - theory1 theory size 2
  - entry: theory3, 10 and 56
  - theory: theory0, linear, 5 and -6
The data are:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

Los candidatos son:
  - la teoría: theory1, square, 7 y 6
  - la entrada: theory3, 7 y 38
  - la entrada: theory3, 4 y 20
  - la entrada: theory3, 9 y 50
  - theory3 el tamaño de la teoría 10
  - la teoría: theory3, mesa, 0 y 0
  - la teoría: theory2, linear, 6 y -4
  - theory0 el tamaño de la teoría 3
  - theory2 el tamaño de la teoría 3
  - la entrada: theory3, 1 y 2
  - theory1 el tamaño de la teoría 2
  - la entrada: theory3, 10 y 56
  - la teoría: theory0, linear, 5 y -6
Los datos son:
  - 9 la observación 50
  - 1 la observación 2
  - 7 la observación 38
  - 4 la observación 20
  - 10 la observación 56
Las reglas son:
  - la regla: a la teoría es lossless si y sólo si it predice every observation exactamente
  - la regla: choose el lossless la teoría de least tamaño
La semántica es: linear la forma y = p1 * x + p2; square la forma y = x * x + p2; constant la forma y = p2; la mesa la forma y = entry(x).
¿Qué smallest lossless la teoría?

候选项如下：
  - 的理论是：theory1、square、7和6
  - 的条目是：theory3、7和38
  - 的条目是：theory3、4和20
  - 的条目是：theory3、9和50
  - theory3的理论规模是10
  - 的理论是：theory3、桌子、0和0
  - 的理论是：theory2、linear、6和-4
  - theory0的理论规模是3
  - theory2的理论规模是3
  - 的条目是：theory3、1和2
  - theory1的理论规模是2
  - 的条目是：theory3、10和56
  - 的理论是：theory0、linear、5和-6
数据如下：
  - 9观察到50
  - 1观察到2
  - 7观察到38
  - 4观察到20
  - 10观察到56
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

Adaylar:
  - kuram: theory1, square, 7 ve 6
  - entry: theory3, 7 ve 38
  - entry: theory3, 4 ve 20
  - entry: theory3, 9 ve 50
  - theory3 10 kuram boyut
  - kuram: theory3, masa, 0 ve 0
  - kuram: theory2, linear, 6 ve -4
  - theory0 3 kuram boyut
  - theory2 3 kuram boyut
  - entry: theory3, 1 ve 2
  - theory1 2 kuram boyut
  - entry: theory3, 10 ve 56
  - kuram: theory0, linear, 5 ve -6
Veriler:
  - 9 50 obs
  - 1 2 obs
  - 7 38 obs
  - 4 20 obs
  - 10 56 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

Wagombea ni:
  - theory: theory1, square, 7 na 6
  - entry: theory3, 7 na 38
  - entry: theory3, 4 na 20
  - entry: theory3, 9 na 50
  - theory3 theory size 10
  - theory: theory3, meza, 0 na 0
  - theory: theory2, linear, 6 na -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 na 2
  - theory1 theory size 2
  - entry: theory3, 10 na 56
  - theory: theory0, linear, 5 na -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

The candidates are:
  - theory: theory1, square, 7 and 6
  - entry: theory3, 7 and 38
  - entry: theory3, 4 and 20
  - entry: theory3, 9 and 50
  - theory3 theory size 10
  - theory: theory3, table, 0 and 0
  - theory: theory2, linear, 6 and -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 and 2
  - theory1 theory size 2
  - entry: theory3, 10 and 56
  - theory: theory0, linear, 5 and -6
The data are:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

{candidates: [(theory theory1 square 7 6) (entry theory3 7 38) (entry theory3 4 20) (entry theory3 9 50) (theory_size theory3 10) (theory theory3 table 0 0) (theory theory2 linear 6 -4) (theory_size theory0 3) (theory_size theory2 3) (entry theory3 1 2) (theory_size theory1 2) (entry theory3 10 56) (theory theory0 linear 5 -6)], data: [(obs 9 50) (obs 1 2) (obs 7 38) (obs 4 20) (obs 10 56)], query: smallest_lossless_theory, rules: [(rule (a_theory_is_lossless_iff_it_predicts_every_observation_exactly)) (rule (choose_the_lossless_theory_of_least_size))], semantics: [(form linear "y = p1 * x + p2") (form square "y = x * x + p2") (form constant "y = p2") (form table "y = entry(x)")]}

Die Kandidaten sind:
  - Theorie: theory1, square, 7 und 6
  - Eintrag: theory3, 7 und 38
  - Eintrag: theory3, 4 und 20
  - Eintrag: theory3, 9 und 50
  - theory3 Theorie Größe 10
  - Theorie: theory3, Tisch, 0 und 0
  - Theorie: theory2, linear, 6 und -4
  - theory0 Theorie Größe 3
  - theory2 Theorie Größe 3
  - Eintrag: theory3, 1 und 2
  - theory1 Theorie Größe 2
  - Eintrag: theory3, 10 und 56
  - Theorie: theory0, linear, 5 und -6
Die Daten sind:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Die Regeln sind:
  - Regel ein Theorie werden verlustfrei gdw. er vorhersagen jeder Beobachtung genau
  - Regel wählen der verlustfrei Theorie aus geringst Größe
Die Semantik ist: linear formen y = p1 * x + p2; square formen y = x * x + p2; constant formen y = p2; der Tisch formen y = entry(x).
Was smallest verlustfrei Theorie?

Кандѝда̄т:
  - тѐо̄рија: theory1, square, 7 и 6
  - одредница: theory3, 7 и 38
  - одредница: theory3, 4 и 20
  - одредница: theory3, 9 и 50
  - theory3 тѐо̄рија величѝна 10
  - тѐо̄рија: theory3, сто̑л, 0 и 0
  - тѐо̄рија: theory2, linear, 6 и -4
  - theory0 тѐо̄рија величѝна 3
  - theory2 тѐо̄рија величѝна 3
  - одредница: theory3, 1 и 2
  - theory1 тѐо̄рија величѝна 2
  - одредница: theory3, 10 и 56
  - тѐо̄рија: theory0, linear, 5 и -6
Податци:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Пра̏вило:
  - пра̏вило тѐо̄рија би̏ти lossless iff оно predvidjeti сва̏кӣ опа́жа̄ње тачно
  - пра̏вило изабрати lossless тѐо̄рија od minimalan величѝна
Сема̀нтика: linear oblik y = p1 * x + p2; square oblik y = x * x + p2; constant oblik y = p2; сто̑л oblik y = entry(x).
Smallest lossless тѐо̄рија kakav?

Ehdokkaat:
  - teoria: theory1, square, 7 ja 6
  - artikkeli: theory3, 7 ja 38
  - artikkeli: theory3, 4 ja 20
  - artikkeli: theory3, 9 ja 50
  - theory3 teoria koko 10
  - teoria: theory3, pöytä, 0 ja 0
  - teoria: theory2, linear, 6 ja -4
  - theory0 teoria koko 3
  - theory2 teoria koko 3
  - artikkeli: theory3, 1 ja 2
  - theory1 teoria koko 2
  - artikkeli: theory3, 10 ja 56
  - teoria: theory0, linear, 5 ja -6
Tieto:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Säännöt:
  - sääntö teoria tulla häviötön joss se ennakoida jokainen havainnointi täsmälleen
  - sääntö valita häviötön teoria vaille vähin koko
Semantiikka: linear muotoilla y = p1 * x + p2; square muotoilla y = x * x + p2; constant muotoilla y = p2; pöytä muotoilla y = entry(x).
Mikä smallest häviötön teoria?

候选项如下：
  - 的理论是：theory1、square、7和6
  - 的条目是：theory3、7和38
  - 的条目是：theory3、4和20
  - 的条目是：theory3、9和50
  - theory3的理论规模是10
  - 的理论是：theory3、桌子、0和0
  - 的理论是：theory2、linear、6和-4
  - theory0的理论规模是3
  - theory2的理论规模是3
  - 的条目是：theory3、1和2
  - theory1的理论规模是2
  - 的条目是：theory3、10和56
  - 的理论是：theory0、linear、5和-6
数据如下：
  - 9观察到50
  - 1观察到2
  - 7观察到38
  - 4观察到20
  - 10观察到56
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

候補者:
  - 理論:theory1, square, 7と6
  - 項目:theory3, 7と38
  - 項目:theory3, 4と20
  - 項目:theory3, 9と50
  - theory310理論大きさ
  - 理論:theory3, 台, 0と0
  - 理論:theory2, linear, 6と-4
  - theory03理論大きさ
  - theory23理論大きさ
  - 項目:theory3, 1と2
  - theory12理論大きさ
  - 項目:theory3, 10と56
  - 理論:theory0, linear, 5と-6
資料:
  - 950obs
  - 12obs
  - 738obs
  - 420obs
  - 1056obs
規則:規則:理論れるロスレスiffこれ予言する凡ゆる観察正確に; 規則:選ぶロスレス理論の中の最小の大きさ.
意味論:lineary = p1 * x + p2形作る; squarey = x * x + p2形作る; constanty = p2形作る; 台y = entry(x)形作る.
smallestロスレス理論何と?

Adaylar:
  - kuram: theory1, square, 7 ve 6
  - entry: theory3, 7 ve 38
  - entry: theory3, 4 ve 20
  - entry: theory3, 9 ve 50
  - theory3 10 kuram boyut
  - kuram: theory3, masa, 0 ve 0
  - kuram: theory2, linear, 6 ve -4
  - theory0 3 kuram boyut
  - theory2 3 kuram boyut
  - entry: theory3, 1 ve 2
  - theory1 2 kuram boyut
  - entry: theory3, 10 ve 56
  - kuram: theory0, linear, 5 ve -6
Veriler:
  - 9 50 obs
  - 1 2 obs
  - 7 38 obs
  - 4 20 obs
  - 10 56 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

مُرَشَّح:
  - نَظَرِيَّة: theory1، square، 7 وَـ 6
  - مَدْخَل: theory3، 7 وَـ 38
  - مَدْخَل: theory3، 4 وَـ 20
  - مَدْخَل: theory3، 9 وَـ 50
  - نَظَرِيَّة مَقَاس theory3 10
  - نَظَرِيَّة: theory3، طَاوِلَة، 0 وَـ 0
  - نَظَرِيَّة: theory2، linear، 6 وَـ -4
  - نَظَرِيَّة مَقَاس theory0 3
  - نَظَرِيَّة مَقَاس theory2 3
  - مَدْخَل: theory3، 1 وَـ 2
  - نَظَرِيَّة مَقَاس theory1 2
  - مَدْخَل: theory3، 10 وَـ 56
  - نَظَرِيَّة: theory0، linear، 5 وَـ -6
بَيَانَات:
  - obs 9 50
  - obs 1 2
  - obs 7 38
  - obs 4 20
  - obs 10 56
قَانُون:
  - قَانُون نَظَرِيَّة كَانَ lossless iff هُوَ تَنَبَّأَ كُلّ رَصْد بِالضَّبْط
  - قَانُون اِخْتَارَ الـ lossless نَظَرِيَّة مِنْ أَقَلَّ مَقَاس
عِلْم اَلْمَعَانِي: شَكَّلَ linear y = p1 * x + p2؛ شَكَّلَ square y = x * x + p2؛ شَكَّلَ constant y = p2؛ شَكَّلَ الـ طَاوِلَة y = entry(x).
smallest lossless نَظَرِيَّة مَاذَا؟

Კანდიდატები:
  - თეორია: theory1, square, 7 და 6
  - სასათაურო სიტყვა: theory3, 7 და 38
  - სასათაურო სიტყვა: theory3, 4 და 20
  - სასათაურო სიტყვა: theory3, 9 და 50
  - theory3 10 თეორია ზომა
  - თეორია: theory3, მაგიდა, 0 და 0
  - თეორია: theory2, linear, 6 და -4
  - theory0 3 თეორია ზომა
  - theory2 3 თეორია ზომა
  - სასათაურო სიტყვა: theory3, 1 და 2
  - theory1 2 თეორია ზომა
  - სასათაურო სიტყვა: theory3, 10 და 56
  - თეორია: theory0, linear, 5 და -6
Მონაცემები:
  - 9 50 obs
  - 1 2 obs
  - 7 38 obs
  - 4 20 obs
  - 10 56 obs
Წესი:
  - წესი თეორია ყოფნა უდანაკარგო iff ის predict ყველა დაკვირვება ზუსტად
  - წესი ამორჩევა უდანაკარგო თეორია of least ზომა
Სემანტიკა: linear y = p1 * x + p2 ბლანკი; square y = x * x + p2 ბლანკი; constant y = p2 ბლანკი; მაგიდა y = entry(x) ბლანკი.
Smallest უდანაკარგო თეორია რა?

Kaiwhakauru:
  - ariā: theory1, square, 7 me 6
  - tāurunga: theory3, 7 me 38
  - tāurunga: theory3, 4 me 20
  - tāurunga: theory3, 9 me 50
  - ariā size theory3 10
  - ariā: theory3, tēpu, 0 me 0
  - ariā: theory2, linear, 6 me -4
  - ariā size theory0 3
  - ariā size theory2 3
  - tāurunga: theory3, 1 me 2
  - ariā size theory1 2
  - tāurunga: theory3, 10 me 56
  - ariā: theory0, linear, 5 me -6
Hōtuku:
  - obs 9 50
  - obs 1 2
  - obs 7 38
  - obs 4 20
  - obs 10 56
Rekureihana:
  - rekureihana ariā is lossless iff it matakite every observation pū
  - rekureihana whiri te lossless ariā o least size
Semantics: āhua linear y = p1 * x + p2; āhua square y = x * x + p2; āhua constant y = p2; āhua te tēpu y = entry(x).
Smallest lossless ariā unutai?

Candidates:
  - lý thuyết: theory1, square, 7 và 6
  - mục từ: theory3, 7 và 38
  - mục từ: theory3, 4 và 20
  - mục từ: theory3, 9 và 50
  - theory3 lý thuyết kích thước 10
  - lý thuyết: theory3, bàn, 0 và 0
  - lý thuyết: theory2, linear, 6 và -4
  - theory0 lý thuyết kích thước 3
  - theory2 lý thuyết kích thước 3
  - mục từ: theory3, 1 và 2
  - theory1 lý thuyết kích thước 2
  - mục từ: theory3, 10 và 56
  - lý thuyết: theory0, linear, 5 và -6
Dữ liệu:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Quy tắc:
  - quy tắc lý thuyết được lossless iff nó dự báo mỗi observation đúng rồi
  - quy tắc chọn the lossless lý thuyết bằng least kích thước
Ngữ nghĩa: linear làm thành y = p1 * x + p2; square làm thành y = x * x + p2; constant làm thành y = p2; bàn làm thành y = entry(x).
Smallest lossless lý thuyết gì?

ผู้สมัคร:
  - ทฤษฎี:theory1, square, 7และ6
  - entry:theory3, 7และ38
  - entry:theory3, 4และ20
  - entry:theory3, 9และ50
  - theory3ทฤษฎีขนาด10
  - ทฤษฎี:theory3, โต๊ะ, 0และ0
  - ทฤษฎี:theory2, linear, 6และ-4
  - theory0ทฤษฎีขนาด3
  - theory2ทฤษฎีขนาด3
  - entry:theory3, 1และ2
  - theory1ทฤษฎีขนาด2
  - entry:theory3, 10และ56
  - ทฤษฎี:theory0, linear, 5และ-6
ข้อมูล:
  - 9obs50
  - 1obs2
  - 7obs38
  - 4obs20
  - 10obs56
กฎ:กฎ:ทฤษฎีถูกlosslessiffมันทำนายทุกการสังเกตexactly; กฎ:เลือกlosslessทฤษฎีของleastขนาด.
อรรถศาสตร์:linearรูปร่างy = p1 * x + p2; squareรูปร่างy = x * x + p2; constantรูปร่างy = p2; โต๊ะรูปร่างy = entry(x).
smallestlosslessทฤษฎีอะไร?

வேட்பாளர்:
  - theory: theory1, square, 7 மற்றும் 6
  - உள்நுழைவதற்கு அனுமதி: theory3, 7 மற்றும் 38
  - உள்நுழைவதற்கு அனுமதி: theory3, 4 மற்றும் 20
  - உள்நுழைவதற்கு அனுமதி: theory3, 9 மற்றும் 50
  - theory3 10 theory size
  - theory: theory3, மேசை, 0 மற்றும் 0
  - theory: theory2, linear, 6 மற்றும் -4
  - theory0 3 theory size
  - theory2 3 theory size
  - உள்நுழைவதற்கு அனுமதி: theory3, 1 மற்றும் 2
  - theory1 2 theory size
  - உள்நுழைவதற்கு அனுமதி: theory3, 10 மற்றும் 56
  - theory: theory0, linear, 5 மற்றும் -6
தரவுகள்:
  - 9 50 obs
  - 1 2 obs
  - 7 38 obs
  - 4 20 obs
  - 10 56 obs
rules: rule theory படு lossless iff it கணி ஒவ்வொரு observation exactly; rule choose lossless theory கொண்ட least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; மேசை y = entry(x) form.
smallest lossless theory என்ன?

Wagombea ni:
  - theory: theory1, square, 7 na 6
  - entry: theory3, 7 na 38
  - entry: theory3, 4 na 20
  - entry: theory3, 9 na 50
  - theory3 theory size 10
  - theory: theory3, meza, 0 na 0
  - theory: theory2, linear, 6 na -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 na 2
  - theory1 theory size 2
  - entry: theory3, 10 na 56
  - theory: theory0, linear, 5 na -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

Candidates:
  - theory: theory1, square, 7 dóó 6
  - entry: theory3, 7 dóó 38
  - entry: theory3, 4 dóó 20
  - entry: theory3, 9 dóó 50
  - theory3 10 theory size
  - theory: theory3, bikááʼ adání, 0 dóó 0
  - theory: theory2, linear, 6 dóó -4
  - theory0 3 theory size
  - theory2 3 theory size
  - entry: theory3, 1 dóó 2
  - theory1 2 theory size
  - entry: theory3, 10 dóó 56
  - theory: theory0, linear, 5 dóó -6
Data:
  - 9 50 obs
  - 1 2 obs
  - 7 38 obs
  - 4 20 obs
  - 10 56 obs
Bee hazʼáanii:
  - bee hazʼáanii theory átʼé lossless iff it predict every observation exactly
  - bee hazʼáanii choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; bikááʼ adání y = entry(x) form.
Smallest lossless theory haʼátʼíísh?

Candidates:
  - theory: theory1, square, 7 aamma 6
  - entry: theory3, 7 aamma 38
  - entry: theory3, 4 aamma 20
  - entry: theory3, 9 aamma 50
  - theory3 10 theory size
  - theory: theory3, table, 0 aamma 0
  - theory: theory2, linear, 6 aamma -4
  - theory0 3 theory size
  - theory2 3 theory size
  - entry: theory3, 1 aamma 2
  - theory1 2 theory size
  - entry: theory3, 10 aamma 56
  - theory: theory0, linear, 5 aamma -6
Data:
  - 9 50 obs
  - 1 2 obs
  - 7 38 obs
  - 4 20 obs
  - 10 56 obs
Rules: rule theory a lossless iff una predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 blanketti; square y = x * x + p2 blanketti; constant y = p2 blanketti; table y = entry(x) blanketti.
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 7 na 6
  - entry: theory3, 7 na 38
  - entry: theory3, 4 na 20
  - entry: theory3, 9 na 50
  - theory3 theory size 10
  - theory: theory3, table, 0 na 0
  - theory: theory2, linear, 6 na -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 na 2
  - theory1 theory size 2
  - entry: theory3, 10 na 56
  - theory: theory0, linear, 5 na -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory bilong least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 7 6
  - entry: theory3, 7 38
  - entry: theory3, 4 20
  - entry: theory3, 9 50
  - theory3 theory size 10
  - theory: theory3, table, 0 0
  - theory: theory2, linear, 6 -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 2
  - theory1 theory size 2
  - entry: theory3, 10 56
  - theory: theory0, linear, 5 -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Nikanixi:
  - nikanixi theory is lossless iff it predict every observation exactly
  - nikanixi choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory kwèch?

Candidates:
  - theory: theory1, square, 7 а 6
  - entry: theory3, 7 а 38
  - entry: theory3, 4 а 20
  - entry: theory3, 9 а 50
  - theory3 theory size 10
  - theory: theory3, table, 0 а 0
  - theory: theory2, linear, 6 а -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 а 2
  - theory1 theory size 2
  - entry: theory3, 10 а 56
  - theory: theory0, linear, 5 а -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Rules:
  - rule theory хила lossless iff it predict дерриг observation exactly
  - rule хержа lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory фу?

후보자:
  - 이론: theory1, square, 7 6
  - 항목: theory3, 7 38
  - 항목: theory3, 4 20
  - 항목: theory3, 9 50
  - theory3 10 이론 크기
  - 이론: theory3, 테이블, 0 0
  - 이론: theory2, linear, 6 -4
  - theory0 3 이론 크기
  - theory2 3 이론 크기
  - 항목: theory3, 1 2
  - theory1 2 이론 크기
  - 항목: theory3, 10 56
  - 이론: theory0, linear, 5 -6
자료:
  - 9 50 obs
  - 1 2 obs
  - 7 38 obs
  - 4 20 obs
  - 10 56 obs
규칙: 규칙 이론 is lossless iff 이것 예언하다 각 관찰 정확하게; 규칙 고르다 lossless 이론...의 가장 적게 크기.
의미론: linear y = p1 * x + p2 형상; square y = x * x + p2 형상; constant y = p2 형상; 테이블 y = entry(x) 형상.
smallest lossless 이론 무엇?

Kandidatu:
  - theory: theory1, square, 7 eta 6
  - sarrera: theory3, 7 eta 38
  - sarrera: theory3, 4 eta 20
  - sarrera: theory3, 9 eta 50
  - theory3 10 theory tamaina
  - theory: theory3, mahai, 0 eta 0
  - theory: theory2, linear, 6 eta -4
  - theory0 3 theory tamaina
  - theory2 3 theory tamaina
  - sarrera: theory3, 1 eta 2
  - theory1 2 theory tamaina
  - sarrera: theory3, 10 eta 56
  - theory: theory0, linear, 5 eta -6
Data:
  - 9 50 obs
  - 1 2 obs
  - 7 38 obs
  - 4 20 obs
  - 10 56 obs
Arau:
  - arau bat theory izan lossless iff it aurresan every observation exactly
  - arau aukeratu the lossless theory of least tamaina
Semantics: linear y = p1 * x + p2 forma; square y = x * x + p2 forma; constant y = p2 forma; mahai y = entry(x) forma.
Smallest lossless theory zer?

ᎠᏙᎩᏯᏍᎩ:
  - theory: theory1, square, 7 ᎠᎴ 6
  - entry: theory3, 7 ᎠᎴ 38
  - entry: theory3, 4 ᎠᎴ 20
  - entry: theory3, 9 ᎠᎴ 50
  - theory3 theory size 10
  - theory: theory3, ᎦᏍᎩᎶ, 0 ᎠᎴ 0
  - theory: theory2, linear, 6 ᎠᎴ -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 ᎠᎴ 2
  - theory1 theory size 2
  - entry: theory3, 10 ᎠᎴ 56
  - theory: theory0, linear, 5 ᎠᎴ -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ᎦᏍᎩᎶ form y = entry(x).
What smallest lossless theory?

Candidates:
  - theory: theory1, square, 7 6
  - entry: theory3, 7 38
  - entry: theory3, 4 20
  - entry: theory3, 9 50
  - theory3 theory chhika 10
  - theory: theory3, patacha, 0 0
  - theory: theory2, linear, 6 -4
  - theory0 theory chhika 3
  - theory2 theory chhika 3
  - entry: theory3, 1 2
  - theory1 theory chhika 2
  - entry: theory3, 10 56
  - theory: theory0, linear, 5 -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Rules:
  - rule theory tiyay lossless iff it predict tukuy observation exactly
  - rule akllay lossless theory of least chhika
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; patacha form y = entry(x).
Smallest lossless theory what?

Candidates:
  - тиориэ: theory1, square, 7 ыкӏи 6
  - entry: theory3, 7 ыкӏи 38
  - entry: theory3, 4 ыкӏи 20
  - entry: theory3, 9 ыкӏи 50
  - theory3 10 тиориэ size
  - тиориэ: theory3, table, 0 ыкӏи 0
  - тиориэ: theory2, linear, 6 ыкӏи -4
  - theory0 3 тиориэ size
  - theory2 3 тиориэ size
  - entry: theory3, 1 ыкӏи 2
  - theory1 2 тиориэ size
  - entry: theory3, 10 ыкӏи 56
  - тиориэ: theory0, linear, 5 ыкӏи -6
Data:
  - 9 50 obs
  - 1 2 obs
  - 7 38 obs
  - 4 20 obs
  - 10 56 obs
Rules: rule тиориэ is lossless iff it predict every observation exactly; rule choose the lossless тиориэ of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless тиориэ сыд?

Candidates:
  - theory: theory1, square, 7 thiab 6
  - entry: theory3, 7 thiab 38
  - entry: theory3, 4 thiab 20
  - entry: theory3, 9 thiab 50
  - theory3 theory size 10
  - theory: theory3, rooj, 0 thiab 0
  - theory: theory2, linear, 6 thiab -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 thiab 2
  - theory1 theory size 2
  - entry: theory3, 10 thiab 56
  - theory: theory0, linear, 5 thiab -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Cai: cai theory is lossless iff nws predict every observation exactly; cai choose lossless theory of least size.
Lub ntsiab: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; rooj form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 7 6
  - entry: theory3, 7 38
  - entry: theory3, 4 20
  - entry: theory3, 9 50
  - theory3 theory size 10
  - theory: theory3, table, 0 0
  - theory: theory2, linear, 6 -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 2
  - theory1 theory size 2
  - entry: theory3, 10 56
  - theory: theory0, linear, 5 -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of wy krook size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory ining-jak?

Candidates:
  - theory: theory1, square, 7 micha' 6
  - entry: theory3, 7 micha' 38
  - entry: theory3, 4 micha' 20
  - entry: theory3, 9 micha' 50
  - theory3 theory size 10
  - theory: theory3, table, 0 micha' 0
  - theory: theory2, linear, 6 micha' -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 micha' 2
  - theory1 theory size 2
  - entry: theory3, 10 micha' 56
  - theory: theory0, linear, 5 micha' -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory nanta?

Candidates:
  - theory: theory1, square, 7 カ 6
  - entry: theory3, 7 カ 38
  - entry: theory3, 4 カ 20
  - entry: theory3, 9 カ 50
  - theory3 10 theory size
  - theory: theory3, table, 0 カ 0
  - theory: theory2, linear, 6 カ -4
  - theory0 3 theory size
  - theory2 3 theory size
  - entry: theory3, 1 カ 2
  - theory1 2 theory size
  - entry: theory3, 10 カ 56
  - theory: theory0, linear, 5 カ -6
Data:
  - 9 50 obs
  - 1 2 obs
  - 7 38 obs
  - 4 20 obs
  - 10 56 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 ノカ; square y = x * x + p2 ノカ; constant y = p2 ノカ; table y = entry(x) ノカ.
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 7 ынкъам 6
  - entry: theory3, 7 ынкъам 38
  - entry: theory3, 4 ынкъам 20
  - entry: theory3, 9 ынкъам 50
  - theory3 theory size 10
  - theory: theory3, table, 0 ынкъам 0
  - theory: theory2, linear, 6 ынкъам -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 ынкъам 2
  - theory1 theory size 2
  - entry: theory3, 10 ынкъам 56
  - theory: theory0, linear, 5 ынкъам -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 7 yéetel 6
  - entry: theory3, 7 yéetel 38
  - entry: theory3, 4 yéetel 20
  - entry: theory3, 9 yéetel 50
  - theory3 theory size 10
  - theory: theory3, table, 0 yéetel 0
  - theory: theory2, linear, 6 yéetel -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 yéetel 2
  - theory1 theory size 2
  - entry: theory3, 10 yéetel 56
  - theory: theory0, linear, 5 yéetel -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Rules:
  - rule theory yan lossless iff it predict every observation exactly
  - rule yéey lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 7 6
  - entry: theory3, 7 38
  - entry: theory3, 4 20
  - entry: theory3, 9 50
  - theory3 theory size 10
  - theory: theory3, mę́soną, 0 0
  - theory: theory2, linear, 6 -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 2
  - theory1 theory size 2
  - entry: theory3, 10 56
  - theory: theory0, linear, 5 -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Rules:
  - rule theory is lossless iff ą́wąną predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mę́soną form y = entry(x).
Smallest lossless theory híli?

Candidates:
  - theory: theory1, square, 7 na 6
  - entry: theory3, 7 na 38
  - entry: theory3, 4 na 20
  - entry: theory3, 9 na 50
  - theory3 10 theory size
  - theory: theory3, table, 0 na 0
  - theory: theory2, linear, 6 na -4
  - theory0 3 theory size
  - theory2 3 theory size
  - entry: theory3, 1 na 2
  - theory1 2 theory size
  - entry: theory3, 10 na 56
  - theory: theory0, linear, 5 na -6
Data:
  - 9 50 obs
  - 1 2 obs
  - 7 38 obs
  - 4 20 obs
  - 10 56 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 7 6
  - entry: theory3, 7 38
  - entry: theory3, 4 20
  - entry: theory3, 9 50
  - theory3 theory size 10
  - theory: theory3, table, 0 0
  - theory: theory2, linear, 6 -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 2
  - theory1 theory size 2
  - entry: theory3, 10 56
  - theory: theory0, linear, 5 -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 7 6
  - entry: theory3, 7 38
  - entry: theory3, 4 20
  - entry: theory3, 9 50
  - theory3 10 theory size
  - theory: theory3, table, 0 0
  - theory: theory2, linear, 6 -4
  - theory0 3 theory size
  - theory2 3 theory size
  - entry: theory3, 1 2
  - theory1 2 theory size
  - entry: theory3, 10 56
  - theory: theory0, linear, 5 -6
Data:
  - 9 50 obs
  - 1 2 obs
  - 7 38 obs
  - 4 20 obs
  - 10 56 obs
Rules:
  - rule maya theory is lossless iff it predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 7 ǂʻá 6
  - entry: theory3, 7 ǂʻá 38
  - entry: theory3, 4 ǂʻá 20
  - entry: theory3, 9 ǂʻá 50
  - theory3 theory ʻǁnàhã 10
  - theory: theory3, table, 0 ǂʻá 0
  - theory: theory2, linear, 6 ǂʻá -4
  - theory0 theory ʻǁnàhã 3
  - theory2 theory ʻǁnàhã 3
  - entry: theory3, 1 ǂʻá 2
  - theory1 theory ʻǁnàhã 2
  - entry: theory3, 10 ǂʻá 56
  - theory: theory0, linear, 5 ǂʻá -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Rules:
  - rule theory ǀîi lossless iff èh predict every observation exactly
  - rule choose lossless theory of least ʻǁnàhã
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 7 6
  - entry: theory3, 7 38
  - entry: theory3, 4 20
  - entry: theory3, 9 50
  - theory3 10 theory size
  - theory: theory3, остол, 0 0
  - theory: theory2, linear, 6 -4
  - theory0 3 theory size
  - theory2 3 theory size
  - entry: theory3, 1 2
  - theory1 2 theory size
  - entry: theory3, 10 56
  - theory: theory0, linear, 5 -6
Data:
  - 9 50 obs
  - 1 2 obs
  - 7 38 obs
  - 4 20 obs
  - 10 56 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; остол y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 7 6
  - entry: theory3, 7 38
  - entry: theory3, 4 20
  - entry: theory3, 9 50
  - theory3 theory size 10
  - theory: theory3, table, 0 0
  - theory: theory2, linear, 6 -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 2
  - theory1 theory size 2
  - entry: theory3, 10 56
  - theory: theory0, linear, 5 -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 7 6
  - entry: theory3, 7 38
  - entry: theory3, 4 20
  - entry: theory3, 9 50
  - theory3 10 theory size
  - theory: theory3, table, 0 0
  - theory: theory2, linear, 6 -4
  - theory0 3 theory size
  - theory2 3 theory size
  - entry: theory3, 1 2
  - theory1 2 theory size
  - entry: theory3, 10 56
  - theory: theory0, linear, 5 -6
Data:
  - 9 50 obs
  - 1 2 obs
  - 7 38 obs
  - 4 20 obs
  - 10 56 obs
Rules:
  - rule theory is lossless iff kitu predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 7 6
  - entry: theory3, 7 38
  - entry: theory3, 4 20
  - entry: theory3, 9 50
  - theory3 theory size 10
  - theory: theory3, mesa, 0 0
  - theory: theory2, linear, 6 -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 2
  - theory1 theory size 2
  - entry: theory3, 10 56
  - theory: theory0, linear, 5 -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mesa form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 7 6
  - entry: theory3, 7 38
  - entry: theory3, 4 20
  - entry: theory3, 9 50
  - theory3 theory size 10
  - theory: theory3, table, 0 0
  - theory: theory2, linear, 6 -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 2
  - theory1 theory size 2
  - entry: theory3, 10 56
  - theory: theory0, linear, 5 -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Rules:
  - rule theory nemi lossless iff yaja predict every observation exactly
  - rule choose ne lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ne table form y = entry(x).
Smallest lossless theory tay?

Les candidats sont:
  - théorie: theory1, square, 7 et 6
  - article: theory3, 7 et 38
  - article: theory3, 4 et 20
  - article: theory3, 9 et 50
  - theory3 théorie taille 10
  - théorie: theory3, table, 0 et 0
  - théorie: theory2, linear, 6 et -4
  - theory0 théorie taille 3
  - theory2 théorie taille 3
  - article: theory3, 1 et 2
  - theory1 théorie taille 2
  - article: theory3, 10 et 56
  - théorie: theory0, linear, 5 et -6
Les données sont:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Les règles sont:
  - règle un théorie être lossless ssi il prédire tout observation exactement
  - règle choisir le lossless théorie du moindre taille
La sémantique est : linear former y = p1 * x + p2 ; square former y = x * x + p2 ; constant former y = p2 ; la table former y = entry(x).
Quoi smallest lossless théorie ?

Kandidato:
  - teorio: theory1, square, 7 kaj 6
  - entry: theory3, 7 kaj 38
  - entry: theory3, 4 kaj 20
  - entry: theory3, 9 kaj 50
  - theory3 teorio grandeco 10
  - teorio: theory3, tablo, 0 kaj 0
  - teorio: theory2, linear, 6 kaj -4
  - theory0 teorio grandeco 3
  - theory2 teorio grandeco 3
  - entry: theory3, 1 kaj 2
  - theory1 teorio grandeco 2
  - entry: theory3, 10 kaj 56
  - teorio: theory0, linear, 5 kaj -6
Datumo:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Regulo: regulo teorio egali lossless iff ĝi predict ĉiu observo ekzakte; regulo elekti lossless teorio de plej malmulta grandeco.
Semantics: linear formi y = p1 * x + p2; square formi y = x * x + p2; constant formi y = p2; tablo formi y = entry(x).
Smallest lossless teorio kio?

Indulók:
  - elmélet: theory1, square, 7 és 6
  - szócikk: theory3, 7 és 38
  - szócikk: theory3, 4 és 20
  - szócikk: theory3, 9 és 50
  - theory3 elmélet méret 10
  - elmélet: theory3, asztal, 0 és 0
  - elmélet: theory2, linear, 6 és -4
  - theory0 elmélet méret 3
  - theory2 elmélet méret 3
  - szócikk: theory3, 1 és 2
  - theory1 elmélet méret 2
  - szócikk: theory3, 10 és 56
  - elmélet: theory0, linear, 5 és -6
Adat:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Szabályok:
  - szabály elmélet van veszteségmentes acsa az megjósol minden megfigyelés pontosan
  - szabály kiválaszt a veszteségmentes elmélet of legkisebb méret
Szemantika: linear kialakít y = p1 * x + p2; square kialakít y = x * x + p2; constant kialakít y = p2; a asztal kialakít y = entry(x).
Smallest veszteségmentes elmélet melyik?

候選人:
  - theory:theory1, square, 7及6
  - entry:theory3, 7及38
  - entry:theory3, 4及20
  - entry:theory3, 9及50
  - theory3theory size10
  - theory:theory3, 檯, 0及0
  - theory:theory2, linear, 6及-4
  - theory0theory size3
  - theory2theory size3
  - entry:theory3, 1及2
  - theory1theory size2
  - entry:theory3, 10及56
  - theory:theory0, linear, 5及-6
數據:
  - 9obs50
  - 1obs2
  - 7obs38
  - 4obs20
  - 10obs56
rules:rule:一theory是losslessiffitpredict每observationexactly; rule:揀losslesstheory...嘅leastsize.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; 檯formy = entry(x).
smallest lossless theory乜嘢?

Candidates:
  - theory: theory1, square, 7 とぅ 6
  - entry: theory3, 7 とぅ 38
  - entry: theory3, 4 とぅ 20
  - entry: theory3, 9 とぅ 50
  - theory3 theory size 10
  - theory: theory3, table, 0 とぅ 0
  - theory: theory2, linear, 6 とぅ -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 とぅ 2
  - theory1 theory size 2
  - entry: theory3, 10 とぅ 56
  - theory: theory0, linear, 5 とぅ -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Rules: rule theory 有ん lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Үміткер:
  - теория: theory1, square, 7 және 6
  - entry: theory3, 7 және 38
  - entry: theory3, 4 және 20
  - entry: theory3, 9 және 50
  - theory3 теория мөлшер 10
  - теория: theory3, үстел, 0 және 0
  - теория: theory2, linear, 6 және -4
  - theory0 теория мөлшер 3
  - theory2 теория мөлшер 3
  - entry: theory3, 1 және 2
  - theory1 теория мөлшер 2
  - entry: theory3, 10 және 56
  - теория: theory0, linear, 5 және -6
Деректер:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Ереже: ереже теория is lossless iff ол predict әр бақылау exactly; ереже таңдау lossless теория туралы least мөлшер.
Семантикалық: linear пішін y = p1 * x + p2; square пішін y = x * x + p2; constant пішін y = p2; үстел пішін y = entry(x).
Smallest lossless теория не?

מועמדת:
  - תּוֹרָה: theory1, square, 7 וְ־ 6
  - entry: theory3, 7 וְ־ 38
  - entry: theory3, 4 וְ־ 20
  - entry: theory3, 9 וְ־ 50
  - theory3 תּוֹרָה גֹּדֶל 10
  - תּוֹרָה: theory3, טַבְלָה, 0 וְ־ 0
  - תּוֹרָה: theory2, linear, 6 וְ־ -4
  - theory0 תּוֹרָה גֹּדֶל 3
  - theory2 תּוֹרָה גֹּדֶל 3
  - entry: theory3, 1 וְ־ 2
  - theory1 תּוֹרָה גֹּדֶל 2
  - entry: theory3, 10 וְ־ 56
  - תּוֹרָה: theory0, linear, 5 וְ־ -6
נְתוּנִים:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
מָשַׁל:
  - מָשַׁל אַחַת תּוֹרָה הוא lossless אםם זֶה predict כֹּל תַּצְפִּית בדיוק
  - מָשַׁל בחר ה־ lossless תּוֹרָה שֶׁל least גֹּדֶל
תורת המשמעים: linear צורה y = p1 * x + p2; square צורה y = x * x + p2; constant צורה y = p2; טַבְלָה ה־ צורה y = entry(x).
איזה smallest lossless תּוֹרָה?

Candidates:
  - theory: theory1, square, 7 დო 6
  - entry: theory3, 7 დო 38
  - entry: theory3, 4 დო 20
  - entry: theory3, 9 დო 50
  - theory3 theory size 10
  - theory: theory3, table, 0 დო 0
  - theory: theory2, linear, 6 დო -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 დო 2
  - theory1 theory size 2
  - entry: theory3, 10 დო 56
  - theory: theory0, linear, 5 დო -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Kandidat:
  - teori: theory1, square, 7 dan 6
  - lema: theory3, 7 dan 38
  - lema: theory3, 4 dan 20
  - lema: theory3, 9 dan 50
  - theory3 teori ukuran 10
  - teori: theory3, meja, 0 dan 0
  - teori: theory2, linear, 6 dan -4
  - theory0 teori ukuran 3
  - theory2 teori ukuran 3
  - lema: theory3, 1 dan 2
  - theory1 teori ukuran 2
  - lema: theory3, 10 dan 56
  - teori: theory0, linear, 5 dan -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Rules:
  - rule teori berada lossless iff it predict setiap observation tepat
  - rule memilih si lossless teori dari least ukuran
Semantik: linear formulir y = p1 * x + p2; square formulir y = x * x + p2; constant formulir y = p2; meja si formulir y = entry(x).
Smallest lossless teori apa?

បេក្ខជន:
  - ទ្រឹស្ដី:theory1, square, 7នឹង6
  - មេពាក្យ:theory3, 7នឹង38
  - មេពាក្យ:theory3, 4នឹង20
  - មេពាក្យ:theory3, 9នឹង50
  - theory3ទ្រឹស្ដីទំហំ10
  - ទ្រឹស្ដី:theory3, តុ, 0នឹង0
  - ទ្រឹស្ដី:theory2, linear, 6នឹង-4
  - theory0ទ្រឹស្ដីទំហំ3
  - theory2ទ្រឹស្ដីទំហំ3
  - មេពាក្យ:theory3, 1នឹង2
  - theory1ទ្រឹស្ដីទំហំ2
  - មេពាក្យ:theory3, 10នឹង56
  - ទ្រឹស្ដី:theory0, linear, 5នឹង-6
ទិន្នន័យ:
  - 9obs50
  - 1obs2
  - 7obs38
  - 4obs20
  - 10obs56
ក្បួន:ក្បួន:ទ្រឹស្ដីត្រូវបានlosslessiffវាចាប់យាមរាល់គំនន់exactly; ក្បួន:រើសthelosslessទ្រឹស្ដីនៃleastទំហំ.
និឃណ្ដសាស្ត្រ:linearគ្រោងy = p1 * x + p2; squareគ្រោងy = x * x + p2; constantគ្រោងy = p2; តុគ្រោងy = entry(x).
smallestlosslessទ្រឹស្ដីអី?

ຜູ້ສະໝັກ:
  - ທິດສະດີ:theory1, square, 7ແລະ6
  - entry:theory3, 7ແລະ38
  - entry:theory3, 4ແລະ20
  - entry:theory3, 9ແລະ50
  - theory3ທິດສະດີຂະຫນາດ10
  - ທິດສະດີ:theory3, ໂຕະ, 0ແລະ0
  - ທິດສະດີ:theory2, linear, 6ແລະ-4
  - theory0ທິດສະດີຂະຫນາດ3
  - theory2ທິດສະດີຂະຫນາດ3
  - entry:theory3, 1ແລະ2
  - theory1ທິດສະດີຂະຫນາດ2
  - entry:theory3, 10ແລະ56
  - ທິດສະດີ:theory0, linear, 5ແລະ-6
ຂໍ້ມູນ:
  - 9obs50
  - 1obs2
  - 7obs38
  - 4obs20
  - 10obs56
ກະຕິກາ:ກະຕິກາ:ທິດສະດີຢູ່losslessiffມັນທຳນວາຍທຸກobservationexactly; ກະຕິກາ:ເລືອກlosslessທິດສະດີຂອງleastຂະຫນາດ.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; ໂຕະformy = entry(x).
smallestlosslessທິດສະດີຫຍັງ?

candidates:
  - theory: theory1, square, 7 మరియు 6
  - entry: theory3, 7 మరియు 38
  - entry: theory3, 4 మరియు 20
  - entry: theory3, 9 మరియు 50
  - theory3 10 theory size
  - theory: theory3, బల్ల, 0 మరియు 0
  - theory: theory2, linear, 6 మరియు -4
  - theory0 3 theory size
  - theory2 3 theory size
  - entry: theory3, 1 మరియు 2
  - theory1 2 theory size
  - entry: theory3, 10 మరియు 56
  - theory: theory0, linear, 5 మరియు -6
data:
  - 9 50 obs
  - 1 2 obs
  - 7 38 obs
  - 4 20 obs
  - 10 56 obs
నియమం: నియమం theory ఉండు lossless iff it predict ప్రతి పరిశీలన exactly; నియమం choose lossless theory of least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; బల్ల y = entry(x) form.
smallest lossless theory ఏమిటి?

Candidates:
  - theory: theory1, square, 7 6
  - entry: theory3, 7 38
  - entry: theory3, 4 20
  - entry: theory3, 9 50
  - theory3 theory size 10
  - theory: theory3, table, 0 0
  - theory: theory2, linear, 6 -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 2
  - theory1 theory size 2
  - entry: theory3, 10 56
  - theory: theory0, linear, 5 -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Rules: rule theory wà lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
What smallest lossless theory?

Candidates:
  - theory: theory1, square, 7 6
  - entry: theory3, 7 38
  - entry: theory3, 4 20
  - entry: theory3, 9 50
  - theory3 10 theory size
  - theory: theory3, table, 0 0
  - theory: theory2, linear, 6 -4
  - theory0 3 theory size
  - theory2 3 theory size
  - entry: theory3, 1 2
  - theory1 2 theory size
  - entry: theory3, 10 56
  - theory: theory0, linear, 5 -6
Data:
  - 9 50 obs
  - 1 2 obs
  - 7 38 obs
  - 4 20 obs
  - 10 56 obs
Rules:
  - rule theory naiágúóli lossless iff it predict every observation exactly
  - rule choose the lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

candidates:
  - theory: theory1, square, 7 6
  - entry: theory3, 7 38
  - entry: theory3, 4 20
  - entry: theory3, 9 50
  - theory3 theory size 10
  - theory: theory3, table, 0 0
  - theory: theory2, linear, 6 -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 2
  - theory1 theory size 2
  - entry: theory3, 10 56
  - theory: theory0, linear, 5 -6
data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
smallest lossless theory what?

Candidates:
  - theory: theory1, square, 7 6
  - entry: theory3, 7 38
  - entry: theory3, 4 20
  - entry: theory3, 9 50
  - theory3 theory size 10
  - theory: theory3, tafra, 0 0
  - theory: theory2, linear, 6 -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 2
  - theory1 theory size 2
  - entry: theory3, 10 56
  - theory: theory0, linear, 5 -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; tafra form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 7 6
  - entry: theory3, 7 38
  - entry: theory3, 4 20
  - entry: theory3, 9 50
  - theory3 theory size 10
  - theory: theory3, táxemésėhestȯtse, 0 0
  - theory: theory2, linear, 6 -4
  - theory0 theory size 3
  - theory2 theory size 3
  - entry: theory3, 1 2
  - theory1 theory size 2
  - entry: theory3, 10 56
  - theory: theory0, linear, 5 -6
Data:
  - 9 obs 50
  - 1 obs 2
  - 7 obs 38
  - 4 obs 20
  - 10 obs 56
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; táxemésėhestȯtse form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 7 6
  - entry: theory3, 7 38
  - entry: theory3, 4 20
  - entry: theory3, 9 50
  - theory3 10 theory size
  - theory: theory3, ствал, 0 0
  - theory: theory2, linear, 6 -4
  - theory0 3 theory size
  - theory2 3 theory size
  - entry: theory3, 1 2
  - theory1 2 theory size
  - entry: theory3, 10 56
  - theory: theory0, linear, 5 -6
Data:
  - 9 50 obs
  - 1 2 obs
  - 7 38 obs
  - 4 20 obs
  - 10 56 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; ствал y = entry(x) form.
Smallest lossless theory вуч?

The candidates are:
  - entry: theory3, 4 and 4
  - entry: theory3, 2 and 0
  - theory: theory3, table, 0 and 0
  - theory0 theory size 3
  - entry: theory3, 9 and 14
  - theory1 theory size 2
  - theory: theory1, square, 6 and 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 and 16
  - theory: theory0, linear, 2 and -4
  - theory: theory2, linear, 0 and -6
  - entry: theory3, 5 and 6
The data are:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

Los candidatos son:
  - la entrada: theory3, 4 y 4
  - la entrada: theory3, 2 y 0
  - la teoría: theory3, mesa, 0 y 0
  - theory0 el tamaño de la teoría 3
  - la entrada: theory3, 9 y 14
  - theory1 el tamaño de la teoría 2
  - la teoría: theory1, square, 6 y 0
  - theory3 el tamaño de la teoría 10
  - theory2 el tamaño de la teoría 3
  - la entrada: theory3, 10 y 16
  - la teoría: theory0, linear, 2 y -4
  - la teoría: theory2, linear, 0 y -6
  - la entrada: theory3, 5 y 6
Los datos son:
  - 5 la observación 6
  - 2 la observación 0
  - 4 la observación 4
  - 10 la observación 16
  - 9 la observación 14
Las reglas son:
  - la regla: a la teoría es lossless si y sólo si it predice every observation exactamente
  - la regla: choose el lossless la teoría de least tamaño
La semántica es: linear la forma y = p1 * x + p2; square la forma y = x * x + p2; constant la forma y = p2; la mesa la forma y = entry(x).
¿Qué smallest lossless la teoría?

候选项如下：
  - 的条目是：theory3、4和4
  - 的条目是：theory3、2和0
  - 的理论是：theory3、桌子、0和0
  - theory0的理论规模是3
  - 的条目是：theory3、9和14
  - theory1的理论规模是2
  - 的理论是：theory1、square、6和0
  - theory3的理论规模是10
  - theory2的理论规模是3
  - 的条目是：theory3、10和16
  - 的理论是：theory0、linear、2和-4
  - 的理论是：theory2、linear、0和-6
  - 的条目是：theory3、5和6
数据如下：
  - 5观察到6
  - 2观察到0
  - 4观察到4
  - 10观察到16
  - 9观察到14
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

Adaylar:
  - entry: theory3, 4 ve 4
  - entry: theory3, 2 ve 0
  - kuram: theory3, masa, 0 ve 0
  - theory0 3 kuram boyut
  - entry: theory3, 9 ve 14
  - theory1 2 kuram boyut
  - kuram: theory1, square, 6 ve 0
  - theory3 10 kuram boyut
  - theory2 3 kuram boyut
  - entry: theory3, 10 ve 16
  - kuram: theory0, linear, 2 ve -4
  - kuram: theory2, linear, 0 ve -6
  - entry: theory3, 5 ve 6
Veriler:
  - 5 6 obs
  - 2 0 obs
  - 4 4 obs
  - 10 16 obs
  - 9 14 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

Wagombea ni:
  - entry: theory3, 4 na 4
  - entry: theory3, 2 na 0
  - theory: theory3, meza, 0 na 0
  - theory0 theory size 3
  - entry: theory3, 9 na 14
  - theory1 theory size 2
  - theory: theory1, square, 6 na 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 na 16
  - theory: theory0, linear, 2 na -4
  - theory: theory2, linear, 0 na -6
  - entry: theory3, 5 na 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

The candidates are:
  - entry: theory3, 4 and 4
  - entry: theory3, 2 and 0
  - theory: theory3, table, 0 and 0
  - theory0 theory size 3
  - entry: theory3, 9 and 14
  - theory1 theory size 2
  - theory: theory1, square, 6 and 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 and 16
  - theory: theory0, linear, 2 and -4
  - theory: theory2, linear, 0 and -6
  - entry: theory3, 5 and 6
The data are:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

{candidates: [(entry theory3 4 4) (entry theory3 2 0) (theory theory3 table 0 0) (theory_size theory0 3) (entry theory3 9 14) (theory_size theory1 2) (theory theory1 square 6 0) (theory_size theory3 10) (theory_size theory2 3) (entry theory3 10 16) (theory theory0 linear 2 -4) (theory theory2 linear 0 -6) (entry theory3 5 6)], data: [(obs 5 6) (obs 2 0) (obs 4 4) (obs 10 16) (obs 9 14)], query: smallest_lossless_theory, rules: [(rule (a_theory_is_lossless_iff_it_predicts_every_observation_exactly)) (rule (choose_the_lossless_theory_of_least_size))], semantics: [(form linear "y = p1 * x + p2") (form square "y = x * x + p2") (form constant "y = p2") (form table "y = entry(x)")]}

Die Kandidaten sind:
  - Eintrag: theory3, 4 und 4
  - Eintrag: theory3, 2 und 0
  - Theorie: theory3, Tisch, 0 und 0
  - theory0 Theorie Größe 3
  - Eintrag: theory3, 9 und 14
  - theory1 Theorie Größe 2
  - Theorie: theory1, square, 6 und 0
  - theory3 Theorie Größe 10
  - theory2 Theorie Größe 3
  - Eintrag: theory3, 10 und 16
  - Theorie: theory0, linear, 2 und -4
  - Theorie: theory2, linear, 0 und -6
  - Eintrag: theory3, 5 und 6
Die Daten sind:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Die Regeln sind:
  - Regel ein Theorie werden verlustfrei gdw. er vorhersagen jeder Beobachtung genau
  - Regel wählen der verlustfrei Theorie aus geringst Größe
Die Semantik ist: linear formen y = p1 * x + p2; square formen y = x * x + p2; constant formen y = p2; der Tisch formen y = entry(x).
Was smallest verlustfrei Theorie?

Кандѝда̄т:
  - одредница: theory3, 4 и 4
  - одредница: theory3, 2 и 0
  - тѐо̄рија: theory3, сто̑л, 0 и 0
  - theory0 тѐо̄рија величѝна 3
  - одредница: theory3, 9 и 14
  - theory1 тѐо̄рија величѝна 2
  - тѐо̄рија: theory1, square, 6 и 0
  - theory3 тѐо̄рија величѝна 10
  - theory2 тѐо̄рија величѝна 3
  - одредница: theory3, 10 и 16
  - тѐо̄рија: theory0, linear, 2 и -4
  - тѐо̄рија: theory2, linear, 0 и -6
  - одредница: theory3, 5 и 6
Податци:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Пра̏вило:
  - пра̏вило тѐо̄рија би̏ти lossless iff оно predvidjeti сва̏кӣ опа́жа̄ње тачно
  - пра̏вило изабрати lossless тѐо̄рија od minimalan величѝна
Сема̀нтика: linear oblik y = p1 * x + p2; square oblik y = x * x + p2; constant oblik y = p2; сто̑л oblik y = entry(x).
Smallest lossless тѐо̄рија kakav?

Ehdokkaat:
  - artikkeli: theory3, 4 ja 4
  - artikkeli: theory3, 2 ja 0
  - teoria: theory3, pöytä, 0 ja 0
  - theory0 teoria koko 3
  - artikkeli: theory3, 9 ja 14
  - theory1 teoria koko 2
  - teoria: theory1, square, 6 ja 0
  - theory3 teoria koko 10
  - theory2 teoria koko 3
  - artikkeli: theory3, 10 ja 16
  - teoria: theory0, linear, 2 ja -4
  - teoria: theory2, linear, 0 ja -6
  - artikkeli: theory3, 5 ja 6
Tieto:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Säännöt:
  - sääntö teoria tulla häviötön joss se ennakoida jokainen havainnointi täsmälleen
  - sääntö valita häviötön teoria vaille vähin koko
Semantiikka: linear muotoilla y = p1 * x + p2; square muotoilla y = x * x + p2; constant muotoilla y = p2; pöytä muotoilla y = entry(x).
Mikä smallest häviötön teoria?

候选项如下：
  - 的条目是：theory3、4和4
  - 的条目是：theory3、2和0
  - 的理论是：theory3、桌子、0和0
  - theory0的理论规模是3
  - 的条目是：theory3、9和14
  - theory1的理论规模是2
  - 的理论是：theory1、square、6和0
  - theory3的理论规模是10
  - theory2的理论规模是3
  - 的条目是：theory3、10和16
  - 的理论是：theory0、linear、2和-4
  - 的理论是：theory2、linear、0和-6
  - 的条目是：theory3、5和6
数据如下：
  - 5观察到6
  - 2观察到0
  - 4观察到4
  - 10观察到16
  - 9观察到14
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

候補者:
  - 項目:theory3, 4と4
  - 項目:theory3, 2と0
  - 理論:theory3, 台, 0と0
  - theory03理論大きさ
  - 項目:theory3, 9と14
  - theory12理論大きさ
  - 理論:theory1, square, 6と0
  - theory310理論大きさ
  - theory23理論大きさ
  - 項目:theory3, 10と16
  - 理論:theory0, linear, 2と-4
  - 理論:theory2, linear, 0と-6
  - 項目:theory3, 5と6
資料:
  - 56obs
  - 20obs
  - 44obs
  - 1016obs
  - 914obs
規則:規則:理論れるロスレスiffこれ予言する凡ゆる観察正確に; 規則:選ぶロスレス理論の中の最小の大きさ.
意味論:lineary = p1 * x + p2形作る; squarey = x * x + p2形作る; constanty = p2形作る; 台y = entry(x)形作る.
smallestロスレス理論何と?

Adaylar:
  - entry: theory3, 4 ve 4
  - entry: theory3, 2 ve 0
  - kuram: theory3, masa, 0 ve 0
  - theory0 3 kuram boyut
  - entry: theory3, 9 ve 14
  - theory1 2 kuram boyut
  - kuram: theory1, square, 6 ve 0
  - theory3 10 kuram boyut
  - theory2 3 kuram boyut
  - entry: theory3, 10 ve 16
  - kuram: theory0, linear, 2 ve -4
  - kuram: theory2, linear, 0 ve -6
  - entry: theory3, 5 ve 6
Veriler:
  - 5 6 obs
  - 2 0 obs
  - 4 4 obs
  - 10 16 obs
  - 9 14 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

مُرَشَّح:
  - مَدْخَل: theory3، 4 وَـ 4
  - مَدْخَل: theory3، 2 وَـ 0
  - نَظَرِيَّة: theory3، طَاوِلَة، 0 وَـ 0
  - نَظَرِيَّة مَقَاس theory0 3
  - مَدْخَل: theory3، 9 وَـ 14
  - نَظَرِيَّة مَقَاس theory1 2
  - نَظَرِيَّة: theory1، square، 6 وَـ 0
  - نَظَرِيَّة مَقَاس theory3 10
  - نَظَرِيَّة مَقَاس theory2 3
  - مَدْخَل: theory3، 10 وَـ 16
  - نَظَرِيَّة: theory0، linear، 2 وَـ -4
  - نَظَرِيَّة: theory2، linear، 0 وَـ -6
  - مَدْخَل: theory3، 5 وَـ 6
بَيَانَات:
  - obs 5 6
  - obs 2 0
  - obs 4 4
  - obs 10 16
  - obs 9 14
قَانُون:
  - قَانُون نَظَرِيَّة كَانَ lossless iff هُوَ تَنَبَّأَ كُلّ رَصْد بِالضَّبْط
  - قَانُون اِخْتَارَ الـ lossless نَظَرِيَّة مِنْ أَقَلَّ مَقَاس
عِلْم اَلْمَعَانِي: شَكَّلَ linear y = p1 * x + p2؛ شَكَّلَ square y = x * x + p2؛ شَكَّلَ constant y = p2؛ شَكَّلَ الـ طَاوِلَة y = entry(x).
smallest lossless نَظَرِيَّة مَاذَا؟

Კანდიდატები:
  - სასათაურო სიტყვა: theory3, 4 და 4
  - სასათაურო სიტყვა: theory3, 2 და 0
  - თეორია: theory3, მაგიდა, 0 და 0
  - theory0 3 თეორია ზომა
  - სასათაურო სიტყვა: theory3, 9 და 14
  - theory1 2 თეორია ზომა
  - თეორია: theory1, square, 6 და 0
  - theory3 10 თეორია ზომა
  - theory2 3 თეორია ზომა
  - სასათაურო სიტყვა: theory3, 10 და 16
  - თეორია: theory0, linear, 2 და -4
  - თეორია: theory2, linear, 0 და -6
  - სასათაურო სიტყვა: theory3, 5 და 6
Მონაცემები:
  - 5 6 obs
  - 2 0 obs
  - 4 4 obs
  - 10 16 obs
  - 9 14 obs
Წესი:
  - წესი თეორია ყოფნა უდანაკარგო iff ის predict ყველა დაკვირვება ზუსტად
  - წესი ამორჩევა უდანაკარგო თეორია of least ზომა
Სემანტიკა: linear y = p1 * x + p2 ბლანკი; square y = x * x + p2 ბლანკი; constant y = p2 ბლანკი; მაგიდა y = entry(x) ბლანკი.
Smallest უდანაკარგო თეორია რა?

Kaiwhakauru:
  - tāurunga: theory3, 4 me 4
  - tāurunga: theory3, 2 me 0
  - ariā: theory3, tēpu, 0 me 0
  - ariā size theory0 3
  - tāurunga: theory3, 9 me 14
  - ariā size theory1 2
  - ariā: theory1, square, 6 me 0
  - ariā size theory3 10
  - ariā size theory2 3
  - tāurunga: theory3, 10 me 16
  - ariā: theory0, linear, 2 me -4
  - ariā: theory2, linear, 0 me -6
  - tāurunga: theory3, 5 me 6
Hōtuku:
  - obs 5 6
  - obs 2 0
  - obs 4 4
  - obs 10 16
  - obs 9 14
Rekureihana:
  - rekureihana ariā is lossless iff it matakite every observation pū
  - rekureihana whiri te lossless ariā o least size
Semantics: āhua linear y = p1 * x + p2; āhua square y = x * x + p2; āhua constant y = p2; āhua te tēpu y = entry(x).
Smallest lossless ariā unutai?

Candidates:
  - mục từ: theory3, 4 và 4
  - mục từ: theory3, 2 và 0
  - lý thuyết: theory3, bàn, 0 và 0
  - theory0 lý thuyết kích thước 3
  - mục từ: theory3, 9 và 14
  - theory1 lý thuyết kích thước 2
  - lý thuyết: theory1, square, 6 và 0
  - theory3 lý thuyết kích thước 10
  - theory2 lý thuyết kích thước 3
  - mục từ: theory3, 10 và 16
  - lý thuyết: theory0, linear, 2 và -4
  - lý thuyết: theory2, linear, 0 và -6
  - mục từ: theory3, 5 và 6
Dữ liệu:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Quy tắc:
  - quy tắc lý thuyết được lossless iff nó dự báo mỗi observation đúng rồi
  - quy tắc chọn the lossless lý thuyết bằng least kích thước
Ngữ nghĩa: linear làm thành y = p1 * x + p2; square làm thành y = x * x + p2; constant làm thành y = p2; bàn làm thành y = entry(x).
Smallest lossless lý thuyết gì?

ผู้สมัคร:
  - entry:theory3, 4และ4
  - entry:theory3, 2และ0
  - ทฤษฎี:theory3, โต๊ะ, 0และ0
  - theory0ทฤษฎีขนาด3
  - entry:theory3, 9และ14
  - theory1ทฤษฎีขนาด2
  - ทฤษฎี:theory1, square, 6และ0
  - theory3ทฤษฎีขนาด10
  - theory2ทฤษฎีขนาด3
  - entry:theory3, 10และ16
  - ทฤษฎี:theory0, linear, 2และ-4
  - ทฤษฎี:theory2, linear, 0และ-6
  - entry:theory3, 5และ6
ข้อมูล:
  - 5obs6
  - 2obs0
  - 4obs4
  - 10obs16
  - 9obs14
กฎ:กฎ:ทฤษฎีถูกlosslessiffมันทำนายทุกการสังเกตexactly; กฎ:เลือกlosslessทฤษฎีของleastขนาด.
อรรถศาสตร์:linearรูปร่างy = p1 * x + p2; squareรูปร่างy = x * x + p2; constantรูปร่างy = p2; โต๊ะรูปร่างy = entry(x).
smallestlosslessทฤษฎีอะไร?

வேட்பாளர்:
  - உள்நுழைவதற்கு அனுமதி: theory3, 4 மற்றும் 4
  - உள்நுழைவதற்கு அனுமதி: theory3, 2 மற்றும் 0
  - theory: theory3, மேசை, 0 மற்றும் 0
  - theory0 3 theory size
  - உள்நுழைவதற்கு அனுமதி: theory3, 9 மற்றும் 14
  - theory1 2 theory size
  - theory: theory1, square, 6 மற்றும் 0
  - theory3 10 theory size
  - theory2 3 theory size
  - உள்நுழைவதற்கு அனுமதி: theory3, 10 மற்றும் 16
  - theory: theory0, linear, 2 மற்றும் -4
  - theory: theory2, linear, 0 மற்றும் -6
  - உள்நுழைவதற்கு அனுமதி: theory3, 5 மற்றும் 6
தரவுகள்:
  - 5 6 obs
  - 2 0 obs
  - 4 4 obs
  - 10 16 obs
  - 9 14 obs
rules: rule theory படு lossless iff it கணி ஒவ்வொரு observation exactly; rule choose lossless theory கொண்ட least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; மேசை y = entry(x) form.
smallest lossless theory என்ன?

Wagombea ni:
  - entry: theory3, 4 na 4
  - entry: theory3, 2 na 0
  - theory: theory3, meza, 0 na 0
  - theory0 theory size 3
  - entry: theory3, 9 na 14
  - theory1 theory size 2
  - theory: theory1, square, 6 na 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 na 16
  - theory: theory0, linear, 2 na -4
  - theory: theory2, linear, 0 na -6
  - entry: theory3, 5 na 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

Candidates:
  - entry: theory3, 4 dóó 4
  - entry: theory3, 2 dóó 0
  - theory: theory3, bikááʼ adání, 0 dóó 0
  - theory0 3 theory size
  - entry: theory3, 9 dóó 14
  - theory1 2 theory size
  - theory: theory1, square, 6 dóó 0
  - theory3 10 theory size
  - theory2 3 theory size
  - entry: theory3, 10 dóó 16
  - theory: theory0, linear, 2 dóó -4
  - theory: theory2, linear, 0 dóó -6
  - entry: theory3, 5 dóó 6
Data:
  - 5 6 obs
  - 2 0 obs
  - 4 4 obs
  - 10 16 obs
  - 9 14 obs
Bee hazʼáanii:
  - bee hazʼáanii theory átʼé lossless iff it predict every observation exactly
  - bee hazʼáanii choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; bikááʼ adání y = entry(x) form.
Smallest lossless theory haʼátʼíísh?

Candidates:
  - entry: theory3, 4 aamma 4
  - entry: theory3, 2 aamma 0
  - theory: theory3, table, 0 aamma 0
  - theory0 3 theory size
  - entry: theory3, 9 aamma 14
  - theory1 2 theory size
  - theory: theory1, square, 6 aamma 0
  - theory3 10 theory size
  - theory2 3 theory size
  - entry: theory3, 10 aamma 16
  - theory: theory0, linear, 2 aamma -4
  - theory: theory2, linear, 0 aamma -6
  - entry: theory3, 5 aamma 6
Data:
  - 5 6 obs
  - 2 0 obs
  - 4 4 obs
  - 10 16 obs
  - 9 14 obs
Rules: rule theory a lossless iff una predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 blanketti; square y = x * x + p2 blanketti; constant y = p2 blanketti; table y = entry(x) blanketti.
Smallest lossless theory what?

Candidates:
  - entry: theory3, 4 na 4
  - entry: theory3, 2 na 0
  - theory: theory3, table, 0 na 0
  - theory0 theory size 3
  - entry: theory3, 9 na 14
  - theory1 theory size 2
  - theory: theory1, square, 6 na 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 na 16
  - theory: theory0, linear, 2 na -4
  - theory: theory2, linear, 0 na -6
  - entry: theory3, 5 na 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory bilong least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory3, 4 4
  - entry: theory3, 2 0
  - theory: theory3, table, 0 0
  - theory0 theory size 3
  - entry: theory3, 9 14
  - theory1 theory size 2
  - theory: theory1, square, 6 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 16
  - theory: theory0, linear, 2 -4
  - theory: theory2, linear, 0 -6
  - entry: theory3, 5 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Nikanixi:
  - nikanixi theory is lossless iff it predict every observation exactly
  - nikanixi choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory kwèch?

Candidates:
  - entry: theory3, 4 а 4
  - entry: theory3, 2 а 0
  - theory: theory3, table, 0 а 0
  - theory0 theory size 3
  - entry: theory3, 9 а 14
  - theory1 theory size 2
  - theory: theory1, square, 6 а 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 а 16
  - theory: theory0, linear, 2 а -4
  - theory: theory2, linear, 0 а -6
  - entry: theory3, 5 а 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Rules:
  - rule theory хила lossless iff it predict дерриг observation exactly
  - rule хержа lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory фу?

후보자:
  - 항목: theory3, 4 4
  - 항목: theory3, 2 0
  - 이론: theory3, 테이블, 0 0
  - theory0 3 이론 크기
  - 항목: theory3, 9 14
  - theory1 2 이론 크기
  - 이론: theory1, square, 6 0
  - theory3 10 이론 크기
  - theory2 3 이론 크기
  - 항목: theory3, 10 16
  - 이론: theory0, linear, 2 -4
  - 이론: theory2, linear, 0 -6
  - 항목: theory3, 5 6
자료:
  - 5 6 obs
  - 2 0 obs
  - 4 4 obs
  - 10 16 obs
  - 9 14 obs
규칙: 규칙 이론 is lossless iff 이것 예언하다 각 관찰 정확하게; 규칙 고르다 lossless 이론...의 가장 적게 크기.
의미론: linear y = p1 * x + p2 형상; square y = x * x + p2 형상; constant y = p2 형상; 테이블 y = entry(x) 형상.
smallest lossless 이론 무엇?

Kandidatu:
  - sarrera: theory3, 4 eta 4
  - sarrera: theory3, 2 eta 0
  - theory: theory3, mahai, 0 eta 0
  - theory0 3 theory tamaina
  - sarrera: theory3, 9 eta 14
  - theory1 2 theory tamaina
  - theory: theory1, square, 6 eta 0
  - theory3 10 theory tamaina
  - theory2 3 theory tamaina
  - sarrera: theory3, 10 eta 16
  - theory: theory0, linear, 2 eta -4
  - theory: theory2, linear, 0 eta -6
  - sarrera: theory3, 5 eta 6
Data:
  - 5 6 obs
  - 2 0 obs
  - 4 4 obs
  - 10 16 obs
  - 9 14 obs
Arau:
  - arau bat theory izan lossless iff it aurresan every observation exactly
  - arau aukeratu the lossless theory of least tamaina
Semantics: linear y = p1 * x + p2 forma; square y = x * x + p2 forma; constant y = p2 forma; mahai y = entry(x) forma.
Smallest lossless theory zer?

ᎠᏙᎩᏯᏍᎩ:
  - entry: theory3, 4 ᎠᎴ 4
  - entry: theory3, 2 ᎠᎴ 0
  - theory: theory3, ᎦᏍᎩᎶ, 0 ᎠᎴ 0
  - theory0 theory size 3
  - entry: theory3, 9 ᎠᎴ 14
  - theory1 theory size 2
  - theory: theory1, square, 6 ᎠᎴ 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 ᎠᎴ 16
  - theory: theory0, linear, 2 ᎠᎴ -4
  - theory: theory2, linear, 0 ᎠᎴ -6
  - entry: theory3, 5 ᎠᎴ 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ᎦᏍᎩᎶ form y = entry(x).
What smallest lossless theory?

Candidates:
  - entry: theory3, 4 4
  - entry: theory3, 2 0
  - theory: theory3, patacha, 0 0
  - theory0 theory chhika 3
  - entry: theory3, 9 14
  - theory1 theory chhika 2
  - theory: theory1, square, 6 0
  - theory3 theory chhika 10
  - theory2 theory chhika 3
  - entry: theory3, 10 16
  - theory: theory0, linear, 2 -4
  - theory: theory2, linear, 0 -6
  - entry: theory3, 5 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Rules:
  - rule theory tiyay lossless iff it predict tukuy observation exactly
  - rule akllay lossless theory of least chhika
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; patacha form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory3, 4 ыкӏи 4
  - entry: theory3, 2 ыкӏи 0
  - тиориэ: theory3, table, 0 ыкӏи 0
  - theory0 3 тиориэ size
  - entry: theory3, 9 ыкӏи 14
  - theory1 2 тиориэ size
  - тиориэ: theory1, square, 6 ыкӏи 0
  - theory3 10 тиориэ size
  - theory2 3 тиориэ size
  - entry: theory3, 10 ыкӏи 16
  - тиориэ: theory0, linear, 2 ыкӏи -4
  - тиориэ: theory2, linear, 0 ыкӏи -6
  - entry: theory3, 5 ыкӏи 6
Data:
  - 5 6 obs
  - 2 0 obs
  - 4 4 obs
  - 10 16 obs
  - 9 14 obs
Rules: rule тиориэ is lossless iff it predict every observation exactly; rule choose the lossless тиориэ of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless тиориэ сыд?

Candidates:
  - entry: theory3, 4 thiab 4
  - entry: theory3, 2 thiab 0
  - theory: theory3, rooj, 0 thiab 0
  - theory0 theory size 3
  - entry: theory3, 9 thiab 14
  - theory1 theory size 2
  - theory: theory1, square, 6 thiab 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 thiab 16
  - theory: theory0, linear, 2 thiab -4
  - theory: theory2, linear, 0 thiab -6
  - entry: theory3, 5 thiab 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Cai: cai theory is lossless iff nws predict every observation exactly; cai choose lossless theory of least size.
Lub ntsiab: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; rooj form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory3, 4 4
  - entry: theory3, 2 0
  - theory: theory3, table, 0 0
  - theory0 theory size 3
  - entry: theory3, 9 14
  - theory1 theory size 2
  - theory: theory1, square, 6 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 16
  - theory: theory0, linear, 2 -4
  - theory: theory2, linear, 0 -6
  - entry: theory3, 5 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of wy krook size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory ining-jak?

Candidates:
  - entry: theory3, 4 micha' 4
  - entry: theory3, 2 micha' 0
  - theory: theory3, table, 0 micha' 0
  - theory0 theory size 3
  - entry: theory3, 9 micha' 14
  - theory1 theory size 2
  - theory: theory1, square, 6 micha' 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 micha' 16
  - theory: theory0, linear, 2 micha' -4
  - theory: theory2, linear, 0 micha' -6
  - entry: theory3, 5 micha' 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory nanta?

Candidates:
  - entry: theory3, 4 カ 4
  - entry: theory3, 2 カ 0
  - theory: theory3, table, 0 カ 0
  - theory0 3 theory size
  - entry: theory3, 9 カ 14
  - theory1 2 theory size
  - theory: theory1, square, 6 カ 0
  - theory3 10 theory size
  - theory2 3 theory size
  - entry: theory3, 10 カ 16
  - theory: theory0, linear, 2 カ -4
  - theory: theory2, linear, 0 カ -6
  - entry: theory3, 5 カ 6
Data:
  - 5 6 obs
  - 2 0 obs
  - 4 4 obs
  - 10 16 obs
  - 9 14 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 ノカ; square y = x * x + p2 ノカ; constant y = p2 ノカ; table y = entry(x) ノカ.
Smallest lossless theory what?

Candidates:
  - entry: theory3, 4 ынкъам 4
  - entry: theory3, 2 ынкъам 0
  - theory: theory3, table, 0 ынкъам 0
  - theory0 theory size 3
  - entry: theory3, 9 ынкъам 14
  - theory1 theory size 2
  - theory: theory1, square, 6 ынкъам 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 ынкъам 16
  - theory: theory0, linear, 2 ынкъам -4
  - theory: theory2, linear, 0 ынкъам -6
  - entry: theory3, 5 ынкъам 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory3, 4 yéetel 4
  - entry: theory3, 2 yéetel 0
  - theory: theory3, table, 0 yéetel 0
  - theory0 theory size 3
  - entry: theory3, 9 yéetel 14
  - theory1 theory size 2
  - theory: theory1, square, 6 yéetel 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 yéetel 16
  - theory: theory0, linear, 2 yéetel -4
  - theory: theory2, linear, 0 yéetel -6
  - entry: theory3, 5 yéetel 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Rules:
  - rule theory yan lossless iff it predict every observation exactly
  - rule yéey lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory3, 4 4
  - entry: theory3, 2 0
  - theory: theory3, mę́soną, 0 0
  - theory0 theory size 3
  - entry: theory3, 9 14
  - theory1 theory size 2
  - theory: theory1, square, 6 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 16
  - theory: theory0, linear, 2 -4
  - theory: theory2, linear, 0 -6
  - entry: theory3, 5 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Rules:
  - rule theory is lossless iff ą́wąną predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mę́soną form y = entry(x).
Smallest lossless theory híli?

Candidates:
  - entry: theory3, 4 na 4
  - entry: theory3, 2 na 0
  - theory: theory3, table, 0 na 0
  - theory0 3 theory size
  - entry: theory3, 9 na 14
  - theory1 2 theory size
  - theory: theory1, square, 6 na 0
  - theory3 10 theory size
  - theory2 3 theory size
  - entry: theory3, 10 na 16
  - theory: theory0, linear, 2 na -4
  - theory: theory2, linear, 0 na -6
  - entry: theory3, 5 na 6
Data:
  - 5 6 obs
  - 2 0 obs
  - 4 4 obs
  - 10 16 obs
  - 9 14 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory3, 4 4
  - entry: theory3, 2 0
  - theory: theory3, table, 0 0
  - theory0 theory size 3
  - entry: theory3, 9 14
  - theory1 theory size 2
  - theory: theory1, square, 6 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 16
  - theory: theory0, linear, 2 -4
  - theory: theory2, linear, 0 -6
  - entry: theory3, 5 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory3, 4 4
  - entry: theory3, 2 0
  - theory: theory3, table, 0 0
  - theory0 3 theory size
  - entry: theory3, 9 14
  - theory1 2 theory size
  - theory: theory1, square, 6 0
  - theory3 10 theory size
  - theory2 3 theory size
  - entry: theory3, 10 16
  - theory: theory0, linear, 2 -4
  - theory: theory2, linear, 0 -6
  - entry: theory3, 5 6
Data:
  - 5 6 obs
  - 2 0 obs
  - 4 4 obs
  - 10 16 obs
  - 9 14 obs
Rules:
  - rule maya theory is lossless iff it predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory3, 4 ǂʻá 4
  - entry: theory3, 2 ǂʻá 0
  - theory: theory3, table, 0 ǂʻá 0
  - theory0 theory ʻǁnàhã 3
  - entry: theory3, 9 ǂʻá 14
  - theory1 theory ʻǁnàhã 2
  - theory: theory1, square, 6 ǂʻá 0
  - theory3 theory ʻǁnàhã 10
  - theory2 theory ʻǁnàhã 3
  - entry: theory3, 10 ǂʻá 16
  - theory: theory0, linear, 2 ǂʻá -4
  - theory: theory2, linear, 0 ǂʻá -6
  - entry: theory3, 5 ǂʻá 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Rules:
  - rule theory ǀîi lossless iff èh predict every observation exactly
  - rule choose lossless theory of least ʻǁnàhã
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory3, 4 4
  - entry: theory3, 2 0
  - theory: theory3, остол, 0 0
  - theory0 3 theory size
  - entry: theory3, 9 14
  - theory1 2 theory size
  - theory: theory1, square, 6 0
  - theory3 10 theory size
  - theory2 3 theory size
  - entry: theory3, 10 16
  - theory: theory0, linear, 2 -4
  - theory: theory2, linear, 0 -6
  - entry: theory3, 5 6
Data:
  - 5 6 obs
  - 2 0 obs
  - 4 4 obs
  - 10 16 obs
  - 9 14 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; остол y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory3, 4 4
  - entry: theory3, 2 0
  - theory: theory3, table, 0 0
  - theory0 theory size 3
  - entry: theory3, 9 14
  - theory1 theory size 2
  - theory: theory1, square, 6 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 16
  - theory: theory0, linear, 2 -4
  - theory: theory2, linear, 0 -6
  - entry: theory3, 5 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory3, 4 4
  - entry: theory3, 2 0
  - theory: theory3, table, 0 0
  - theory0 3 theory size
  - entry: theory3, 9 14
  - theory1 2 theory size
  - theory: theory1, square, 6 0
  - theory3 10 theory size
  - theory2 3 theory size
  - entry: theory3, 10 16
  - theory: theory0, linear, 2 -4
  - theory: theory2, linear, 0 -6
  - entry: theory3, 5 6
Data:
  - 5 6 obs
  - 2 0 obs
  - 4 4 obs
  - 10 16 obs
  - 9 14 obs
Rules:
  - rule theory is lossless iff kitu predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory3, 4 4
  - entry: theory3, 2 0
  - theory: theory3, mesa, 0 0
  - theory0 theory size 3
  - entry: theory3, 9 14
  - theory1 theory size 2
  - theory: theory1, square, 6 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 16
  - theory: theory0, linear, 2 -4
  - theory: theory2, linear, 0 -6
  - entry: theory3, 5 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mesa form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory3, 4 4
  - entry: theory3, 2 0
  - theory: theory3, table, 0 0
  - theory0 theory size 3
  - entry: theory3, 9 14
  - theory1 theory size 2
  - theory: theory1, square, 6 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 16
  - theory: theory0, linear, 2 -4
  - theory: theory2, linear, 0 -6
  - entry: theory3, 5 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Rules:
  - rule theory nemi lossless iff yaja predict every observation exactly
  - rule choose ne lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ne table form y = entry(x).
Smallest lossless theory tay?

Les candidats sont:
  - article: theory3, 4 et 4
  - article: theory3, 2 et 0
  - théorie: theory3, table, 0 et 0
  - theory0 théorie taille 3
  - article: theory3, 9 et 14
  - theory1 théorie taille 2
  - théorie: theory1, square, 6 et 0
  - theory3 théorie taille 10
  - theory2 théorie taille 3
  - article: theory3, 10 et 16
  - théorie: theory0, linear, 2 et -4
  - théorie: theory2, linear, 0 et -6
  - article: theory3, 5 et 6
Les données sont:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Les règles sont:
  - règle un théorie être lossless ssi il prédire tout observation exactement
  - règle choisir le lossless théorie du moindre taille
La sémantique est : linear former y = p1 * x + p2 ; square former y = x * x + p2 ; constant former y = p2 ; la table former y = entry(x).
Quoi smallest lossless théorie ?

Kandidato:
  - entry: theory3, 4 kaj 4
  - entry: theory3, 2 kaj 0
  - teorio: theory3, tablo, 0 kaj 0
  - theory0 teorio grandeco 3
  - entry: theory3, 9 kaj 14
  - theory1 teorio grandeco 2
  - teorio: theory1, square, 6 kaj 0
  - theory3 teorio grandeco 10
  - theory2 teorio grandeco 3
  - entry: theory3, 10 kaj 16
  - teorio: theory0, linear, 2 kaj -4
  - teorio: theory2, linear, 0 kaj -6
  - entry: theory3, 5 kaj 6
Datumo:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Regulo: regulo teorio egali lossless iff ĝi predict ĉiu observo ekzakte; regulo elekti lossless teorio de plej malmulta grandeco.
Semantics: linear formi y = p1 * x + p2; square formi y = x * x + p2; constant formi y = p2; tablo formi y = entry(x).
Smallest lossless teorio kio?

Indulók:
  - szócikk: theory3, 4 és 4
  - szócikk: theory3, 2 és 0
  - elmélet: theory3, asztal, 0 és 0
  - theory0 elmélet méret 3
  - szócikk: theory3, 9 és 14
  - theory1 elmélet méret 2
  - elmélet: theory1, square, 6 és 0
  - theory3 elmélet méret 10
  - theory2 elmélet méret 3
  - szócikk: theory3, 10 és 16
  - elmélet: theory0, linear, 2 és -4
  - elmélet: theory2, linear, 0 és -6
  - szócikk: theory3, 5 és 6
Adat:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Szabályok:
  - szabály elmélet van veszteségmentes acsa az megjósol minden megfigyelés pontosan
  - szabály kiválaszt a veszteségmentes elmélet of legkisebb méret
Szemantika: linear kialakít y = p1 * x + p2; square kialakít y = x * x + p2; constant kialakít y = p2; a asztal kialakít y = entry(x).
Smallest veszteségmentes elmélet melyik?

候選人:
  - entry:theory3, 4及4
  - entry:theory3, 2及0
  - theory:theory3, 檯, 0及0
  - theory0theory size3
  - entry:theory3, 9及14
  - theory1theory size2
  - theory:theory1, square, 6及0
  - theory3theory size10
  - theory2theory size3
  - entry:theory3, 10及16
  - theory:theory0, linear, 2及-4
  - theory:theory2, linear, 0及-6
  - entry:theory3, 5及6
數據:
  - 5obs6
  - 2obs0
  - 4obs4
  - 10obs16
  - 9obs14
rules:rule:一theory是losslessiffitpredict每observationexactly; rule:揀losslesstheory...嘅leastsize.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; 檯formy = entry(x).
smallest lossless theory乜嘢?

Candidates:
  - entry: theory3, 4 とぅ 4
  - entry: theory3, 2 とぅ 0
  - theory: theory3, table, 0 とぅ 0
  - theory0 theory size 3
  - entry: theory3, 9 とぅ 14
  - theory1 theory size 2
  - theory: theory1, square, 6 とぅ 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 とぅ 16
  - theory: theory0, linear, 2 とぅ -4
  - theory: theory2, linear, 0 とぅ -6
  - entry: theory3, 5 とぅ 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Rules: rule theory 有ん lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Үміткер:
  - entry: theory3, 4 және 4
  - entry: theory3, 2 және 0
  - теория: theory3, үстел, 0 және 0
  - theory0 теория мөлшер 3
  - entry: theory3, 9 және 14
  - theory1 теория мөлшер 2
  - теория: theory1, square, 6 және 0
  - theory3 теория мөлшер 10
  - theory2 теория мөлшер 3
  - entry: theory3, 10 және 16
  - теория: theory0, linear, 2 және -4
  - теория: theory2, linear, 0 және -6
  - entry: theory3, 5 және 6
Деректер:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Ереже: ереже теория is lossless iff ол predict әр бақылау exactly; ереже таңдау lossless теория туралы least мөлшер.
Семантикалық: linear пішін y = p1 * x + p2; square пішін y = x * x + p2; constant пішін y = p2; үстел пішін y = entry(x).
Smallest lossless теория не?

מועמדת:
  - entry: theory3, 4 וְ־ 4
  - entry: theory3, 2 וְ־ 0
  - תּוֹרָה: theory3, טַבְלָה, 0 וְ־ 0
  - theory0 תּוֹרָה גֹּדֶל 3
  - entry: theory3, 9 וְ־ 14
  - theory1 תּוֹרָה גֹּדֶל 2
  - תּוֹרָה: theory1, square, 6 וְ־ 0
  - theory3 תּוֹרָה גֹּדֶל 10
  - theory2 תּוֹרָה גֹּדֶל 3
  - entry: theory3, 10 וְ־ 16
  - תּוֹרָה: theory0, linear, 2 וְ־ -4
  - תּוֹרָה: theory2, linear, 0 וְ־ -6
  - entry: theory3, 5 וְ־ 6
נְתוּנִים:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
מָשַׁל:
  - מָשַׁל אַחַת תּוֹרָה הוא lossless אםם זֶה predict כֹּל תַּצְפִּית בדיוק
  - מָשַׁל בחר ה־ lossless תּוֹרָה שֶׁל least גֹּדֶל
תורת המשמעים: linear צורה y = p1 * x + p2; square צורה y = x * x + p2; constant צורה y = p2; טַבְלָה ה־ צורה y = entry(x).
איזה smallest lossless תּוֹרָה?

Candidates:
  - entry: theory3, 4 დო 4
  - entry: theory3, 2 დო 0
  - theory: theory3, table, 0 დო 0
  - theory0 theory size 3
  - entry: theory3, 9 დო 14
  - theory1 theory size 2
  - theory: theory1, square, 6 დო 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 დო 16
  - theory: theory0, linear, 2 დო -4
  - theory: theory2, linear, 0 დო -6
  - entry: theory3, 5 დო 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Kandidat:
  - lema: theory3, 4 dan 4
  - lema: theory3, 2 dan 0
  - teori: theory3, meja, 0 dan 0
  - theory0 teori ukuran 3
  - lema: theory3, 9 dan 14
  - theory1 teori ukuran 2
  - teori: theory1, square, 6 dan 0
  - theory3 teori ukuran 10
  - theory2 teori ukuran 3
  - lema: theory3, 10 dan 16
  - teori: theory0, linear, 2 dan -4
  - teori: theory2, linear, 0 dan -6
  - lema: theory3, 5 dan 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Rules:
  - rule teori berada lossless iff it predict setiap observation tepat
  - rule memilih si lossless teori dari least ukuran
Semantik: linear formulir y = p1 * x + p2; square formulir y = x * x + p2; constant formulir y = p2; meja si formulir y = entry(x).
Smallest lossless teori apa?

បេក្ខជន:
  - មេពាក្យ:theory3, 4នឹង4
  - មេពាក្យ:theory3, 2នឹង0
  - ទ្រឹស្ដី:theory3, តុ, 0នឹង0
  - theory0ទ្រឹស្ដីទំហំ3
  - មេពាក្យ:theory3, 9នឹង14
  - theory1ទ្រឹស្ដីទំហំ2
  - ទ្រឹស្ដី:theory1, square, 6នឹង0
  - theory3ទ្រឹស្ដីទំហំ10
  - theory2ទ្រឹស្ដីទំហំ3
  - មេពាក្យ:theory3, 10នឹង16
  - ទ្រឹស្ដី:theory0, linear, 2នឹង-4
  - ទ្រឹស្ដី:theory2, linear, 0នឹង-6
  - មេពាក្យ:theory3, 5នឹង6
ទិន្នន័យ:
  - 5obs6
  - 2obs0
  - 4obs4
  - 10obs16
  - 9obs14
ក្បួន:ក្បួន:ទ្រឹស្ដីត្រូវបានlosslessiffវាចាប់យាមរាល់គំនន់exactly; ក្បួន:រើសthelosslessទ្រឹស្ដីនៃleastទំហំ.
និឃណ្ដសាស្ត្រ:linearគ្រោងy = p1 * x + p2; squareគ្រោងy = x * x + p2; constantគ្រោងy = p2; តុគ្រោងy = entry(x).
smallestlosslessទ្រឹស្ដីអី?

ຜູ້ສະໝັກ:
  - entry:theory3, 4ແລະ4
  - entry:theory3, 2ແລະ0
  - ທິດສະດີ:theory3, ໂຕະ, 0ແລະ0
  - theory0ທິດສະດີຂະຫນາດ3
  - entry:theory3, 9ແລະ14
  - theory1ທິດສະດີຂະຫນາດ2
  - ທິດສະດີ:theory1, square, 6ແລະ0
  - theory3ທິດສະດີຂະຫນາດ10
  - theory2ທິດສະດີຂະຫນາດ3
  - entry:theory3, 10ແລະ16
  - ທິດສະດີ:theory0, linear, 2ແລະ-4
  - ທິດສະດີ:theory2, linear, 0ແລະ-6
  - entry:theory3, 5ແລະ6
ຂໍ້ມູນ:
  - 5obs6
  - 2obs0
  - 4obs4
  - 10obs16
  - 9obs14
ກະຕິກາ:ກະຕິກາ:ທິດສະດີຢູ່losslessiffມັນທຳນວາຍທຸກobservationexactly; ກະຕິກາ:ເລືອກlosslessທິດສະດີຂອງleastຂະຫນາດ.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; ໂຕະformy = entry(x).
smallestlosslessທິດສະດີຫຍັງ?

candidates:
  - entry: theory3, 4 మరియు 4
  - entry: theory3, 2 మరియు 0
  - theory: theory3, బల్ల, 0 మరియు 0
  - theory0 3 theory size
  - entry: theory3, 9 మరియు 14
  - theory1 2 theory size
  - theory: theory1, square, 6 మరియు 0
  - theory3 10 theory size
  - theory2 3 theory size
  - entry: theory3, 10 మరియు 16
  - theory: theory0, linear, 2 మరియు -4
  - theory: theory2, linear, 0 మరియు -6
  - entry: theory3, 5 మరియు 6
data:
  - 5 6 obs
  - 2 0 obs
  - 4 4 obs
  - 10 16 obs
  - 9 14 obs
నియమం: నియమం theory ఉండు lossless iff it predict ప్రతి పరిశీలన exactly; నియమం choose lossless theory of least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; బల్ల y = entry(x) form.
smallest lossless theory ఏమిటి?

Candidates:
  - entry: theory3, 4 4
  - entry: theory3, 2 0
  - theory: theory3, table, 0 0
  - theory0 theory size 3
  - entry: theory3, 9 14
  - theory1 theory size 2
  - theory: theory1, square, 6 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 16
  - theory: theory0, linear, 2 -4
  - theory: theory2, linear, 0 -6
  - entry: theory3, 5 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Rules: rule theory wà lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
What smallest lossless theory?

Candidates:
  - entry: theory3, 4 4
  - entry: theory3, 2 0
  - theory: theory3, table, 0 0
  - theory0 3 theory size
  - entry: theory3, 9 14
  - theory1 2 theory size
  - theory: theory1, square, 6 0
  - theory3 10 theory size
  - theory2 3 theory size
  - entry: theory3, 10 16
  - theory: theory0, linear, 2 -4
  - theory: theory2, linear, 0 -6
  - entry: theory3, 5 6
Data:
  - 5 6 obs
  - 2 0 obs
  - 4 4 obs
  - 10 16 obs
  - 9 14 obs
Rules:
  - rule theory naiágúóli lossless iff it predict every observation exactly
  - rule choose the lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

candidates:
  - entry: theory3, 4 4
  - entry: theory3, 2 0
  - theory: theory3, table, 0 0
  - theory0 theory size 3
  - entry: theory3, 9 14
  - theory1 theory size 2
  - theory: theory1, square, 6 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 16
  - theory: theory0, linear, 2 -4
  - theory: theory2, linear, 0 -6
  - entry: theory3, 5 6
data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
smallest lossless theory what?

Candidates:
  - entry: theory3, 4 4
  - entry: theory3, 2 0
  - theory: theory3, tafra, 0 0
  - theory0 theory size 3
  - entry: theory3, 9 14
  - theory1 theory size 2
  - theory: theory1, square, 6 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 16
  - theory: theory0, linear, 2 -4
  - theory: theory2, linear, 0 -6
  - entry: theory3, 5 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; tafra form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory3, 4 4
  - entry: theory3, 2 0
  - theory: theory3, táxemésėhestȯtse, 0 0
  - theory0 theory size 3
  - entry: theory3, 9 14
  - theory1 theory size 2
  - theory: theory1, square, 6 0
  - theory3 theory size 10
  - theory2 theory size 3
  - entry: theory3, 10 16
  - theory: theory0, linear, 2 -4
  - theory: theory2, linear, 0 -6
  - entry: theory3, 5 6
Data:
  - 5 obs 6
  - 2 obs 0
  - 4 obs 4
  - 10 obs 16
  - 9 obs 14
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; táxemésėhestȯtse form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory3, 4 4
  - entry: theory3, 2 0
  - theory: theory3, ствал, 0 0
  - theory0 3 theory size
  - entry: theory3, 9 14
  - theory1 2 theory size
  - theory: theory1, square, 6 0
  - theory3 10 theory size
  - theory2 3 theory size
  - entry: theory3, 10 16
  - theory: theory0, linear, 2 -4
  - theory: theory2, linear, 0 -6
  - entry: theory3, 5 6
Data:
  - 5 6 obs
  - 2 0 obs
  - 4 4 obs
  - 10 16 obs
  - 9 14 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; ствал y = entry(x) form.
Smallest lossless theory вуч?

The candidates are:
  - entry: theory1, 11 and 64
  - entry: theory1, 1 and 4
  - theory: theory0, linear, 8 and 0
  - entry: theory1, 9 and 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 and -2
  - theory: theory1, table, 0 and 0
  - entry: theory1, 5 and 28
  - theory: theory3, square, 6 and -6
  - entry: theory1, 7 and 40
  - theory3 theory size 2
The data are:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

Los candidatos son:
  - la entrada: theory1, 11 y 64
  - la entrada: theory1, 1 y 4
  - la teoría: theory0, linear, 8 y 0
  - la entrada: theory1, 9 y 52
  - theory2 el tamaño de la teoría 3
  - theory1 el tamaño de la teoría 10
  - theory0 el tamaño de la teoría 3
  - la teoría: theory2, linear, 6 y -2
  - la teoría: theory1, mesa, 0 y 0
  - la entrada: theory1, 5 y 28
  - la teoría: theory3, square, 6 y -6
  - la entrada: theory1, 7 y 40
  - theory3 el tamaño de la teoría 2
Los datos son:
  - 7 la observación 40
  - 5 la observación 28
  - 9 la observación 52
  - 11 la observación 64
  - 1 la observación 4
Las reglas son:
  - la regla: a la teoría es lossless si y sólo si it predice every observation exactamente
  - la regla: choose el lossless la teoría de least tamaño
La semántica es: linear la forma y = p1 * x + p2; square la forma y = x * x + p2; constant la forma y = p2; la mesa la forma y = entry(x).
¿Qué smallest lossless la teoría?

候选项如下：
  - 的条目是：theory1、11和64
  - 的条目是：theory1、1和4
  - 的理论是：theory0、linear、8和0
  - 的条目是：theory1、9和52
  - theory2的理论规模是3
  - theory1的理论规模是10
  - theory0的理论规模是3
  - 的理论是：theory2、linear、6和-2
  - 的理论是：theory1、桌子、0和0
  - 的条目是：theory1、5和28
  - 的理论是：theory3、square、6和-6
  - 的条目是：theory1、7和40
  - theory3的理论规模是2
数据如下：
  - 7观察到40
  - 5观察到28
  - 9观察到52
  - 11观察到64
  - 1观察到4
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

Adaylar:
  - entry: theory1, 11 ve 64
  - entry: theory1, 1 ve 4
  - kuram: theory0, linear, 8 ve 0
  - entry: theory1, 9 ve 52
  - theory2 3 kuram boyut
  - theory1 10 kuram boyut
  - theory0 3 kuram boyut
  - kuram: theory2, linear, 6 ve -2
  - kuram: theory1, masa, 0 ve 0
  - entry: theory1, 5 ve 28
  - kuram: theory3, square, 6 ve -6
  - entry: theory1, 7 ve 40
  - theory3 2 kuram boyut
Veriler:
  - 7 40 obs
  - 5 28 obs
  - 9 52 obs
  - 11 64 obs
  - 1 4 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

Wagombea ni:
  - entry: theory1, 11 na 64
  - entry: theory1, 1 na 4
  - theory: theory0, linear, 8 na 0
  - entry: theory1, 9 na 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 na -2
  - theory: theory1, meza, 0 na 0
  - entry: theory1, 5 na 28
  - theory: theory3, square, 6 na -6
  - entry: theory1, 7 na 40
  - theory3 theory size 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

The candidates are:
  - entry: theory1, 11 and 64
  - entry: theory1, 1 and 4
  - theory: theory0, linear, 8 and 0
  - entry: theory1, 9 and 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 and -2
  - theory: theory1, table, 0 and 0
  - entry: theory1, 5 and 28
  - theory: theory3, square, 6 and -6
  - entry: theory1, 7 and 40
  - theory3 theory size 2
The data are:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

{candidates: [(entry theory1 11 64) (entry theory1 1 4) (theory theory0 linear 8 0) (entry theory1 9 52) (theory_size theory2 3) (theory_size theory1 10) (theory_size theory0 3) (theory theory2 linear 6 -2) (theory theory1 table 0 0) (entry theory1 5 28) (theory theory3 square 6 -6) (entry theory1 7 40) (theory_size theory3 2)], data: [(obs 7 40) (obs 5 28) (obs 9 52) (obs 11 64) (obs 1 4)], query: smallest_lossless_theory, rules: [(rule (a_theory_is_lossless_iff_it_predicts_every_observation_exactly)) (rule (choose_the_lossless_theory_of_least_size))], semantics: [(form linear "y = p1 * x + p2") (form square "y = x * x + p2") (form constant "y = p2") (form table "y = entry(x)")]}

Die Kandidaten sind:
  - Eintrag: theory1, 11 und 64
  - Eintrag: theory1, 1 und 4
  - Theorie: theory0, linear, 8 und 0
  - Eintrag: theory1, 9 und 52
  - theory2 Theorie Größe 3
  - theory1 Theorie Größe 10
  - theory0 Theorie Größe 3
  - Theorie: theory2, linear, 6 und -2
  - Theorie: theory1, Tisch, 0 und 0
  - Eintrag: theory1, 5 und 28
  - Theorie: theory3, square, 6 und -6
  - Eintrag: theory1, 7 und 40
  - theory3 Theorie Größe 2
Die Daten sind:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Die Regeln sind:
  - Regel ein Theorie werden verlustfrei gdw. er vorhersagen jeder Beobachtung genau
  - Regel wählen der verlustfrei Theorie aus geringst Größe
Die Semantik ist: linear formen y = p1 * x + p2; square formen y = x * x + p2; constant formen y = p2; der Tisch formen y = entry(x).
Was smallest verlustfrei Theorie?

Кандѝда̄т:
  - одредница: theory1, 11 и 64
  - одредница: theory1, 1 и 4
  - тѐо̄рија: theory0, linear, 8 и 0
  - одредница: theory1, 9 и 52
  - theory2 тѐо̄рија величѝна 3
  - theory1 тѐо̄рија величѝна 10
  - theory0 тѐо̄рија величѝна 3
  - тѐо̄рија: theory2, linear, 6 и -2
  - тѐо̄рија: theory1, сто̑л, 0 и 0
  - одредница: theory1, 5 и 28
  - тѐо̄рија: theory3, square, 6 и -6
  - одредница: theory1, 7 и 40
  - theory3 тѐо̄рија величѝна 2
Податци:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Пра̏вило:
  - пра̏вило тѐо̄рија би̏ти lossless iff оно predvidjeti сва̏кӣ опа́жа̄ње тачно
  - пра̏вило изабрати lossless тѐо̄рија od minimalan величѝна
Сема̀нтика: linear oblik y = p1 * x + p2; square oblik y = x * x + p2; constant oblik y = p2; сто̑л oblik y = entry(x).
Smallest lossless тѐо̄рија kakav?

Ehdokkaat:
  - artikkeli: theory1, 11 ja 64
  - artikkeli: theory1, 1 ja 4
  - teoria: theory0, linear, 8 ja 0
  - artikkeli: theory1, 9 ja 52
  - theory2 teoria koko 3
  - theory1 teoria koko 10
  - theory0 teoria koko 3
  - teoria: theory2, linear, 6 ja -2
  - teoria: theory1, pöytä, 0 ja 0
  - artikkeli: theory1, 5 ja 28
  - teoria: theory3, square, 6 ja -6
  - artikkeli: theory1, 7 ja 40
  - theory3 teoria koko 2
Tieto:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Säännöt:
  - sääntö teoria tulla häviötön joss se ennakoida jokainen havainnointi täsmälleen
  - sääntö valita häviötön teoria vaille vähin koko
Semantiikka: linear muotoilla y = p1 * x + p2; square muotoilla y = x * x + p2; constant muotoilla y = p2; pöytä muotoilla y = entry(x).
Mikä smallest häviötön teoria?

候选项如下：
  - 的条目是：theory1、11和64
  - 的条目是：theory1、1和4
  - 的理论是：theory0、linear、8和0
  - 的条目是：theory1、9和52
  - theory2的理论规模是3
  - theory1的理论规模是10
  - theory0的理论规模是3
  - 的理论是：theory2、linear、6和-2
  - 的理论是：theory1、桌子、0和0
  - 的条目是：theory1、5和28
  - 的理论是：theory3、square、6和-6
  - 的条目是：theory1、7和40
  - theory3的理论规模是2
数据如下：
  - 7观察到40
  - 5观察到28
  - 9观察到52
  - 11观察到64
  - 1观察到4
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

候補者:
  - 項目:theory1, 11と64
  - 項目:theory1, 1と4
  - 理論:theory0, linear, 8と0
  - 項目:theory1, 9と52
  - theory23理論大きさ
  - theory110理論大きさ
  - theory03理論大きさ
  - 理論:theory2, linear, 6と-2
  - 理論:theory1, 台, 0と0
  - 項目:theory1, 5と28
  - 理論:theory3, square, 6と-6
  - 項目:theory1, 7と40
  - theory32理論大きさ
資料:
  - 740obs
  - 528obs
  - 952obs
  - 1164obs
  - 14obs
規則:規則:理論れるロスレスiffこれ予言する凡ゆる観察正確に; 規則:選ぶロスレス理論の中の最小の大きさ.
意味論:lineary = p1 * x + p2形作る; squarey = x * x + p2形作る; constanty = p2形作る; 台y = entry(x)形作る.
smallestロスレス理論何と?

Adaylar:
  - entry: theory1, 11 ve 64
  - entry: theory1, 1 ve 4
  - kuram: theory0, linear, 8 ve 0
  - entry: theory1, 9 ve 52
  - theory2 3 kuram boyut
  - theory1 10 kuram boyut
  - theory0 3 kuram boyut
  - kuram: theory2, linear, 6 ve -2
  - kuram: theory1, masa, 0 ve 0
  - entry: theory1, 5 ve 28
  - kuram: theory3, square, 6 ve -6
  - entry: theory1, 7 ve 40
  - theory3 2 kuram boyut
Veriler:
  - 7 40 obs
  - 5 28 obs
  - 9 52 obs
  - 11 64 obs
  - 1 4 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

مُرَشَّح:
  - مَدْخَل: theory1، 11 وَـ 64
  - مَدْخَل: theory1، 1 وَـ 4
  - نَظَرِيَّة: theory0، linear، 8 وَـ 0
  - مَدْخَل: theory1، 9 وَـ 52
  - نَظَرِيَّة مَقَاس theory2 3
  - نَظَرِيَّة مَقَاس theory1 10
  - نَظَرِيَّة مَقَاس theory0 3
  - نَظَرِيَّة: theory2، linear، 6 وَـ -2
  - نَظَرِيَّة: theory1، طَاوِلَة، 0 وَـ 0
  - مَدْخَل: theory1، 5 وَـ 28
  - نَظَرِيَّة: theory3، square، 6 وَـ -6
  - مَدْخَل: theory1، 7 وَـ 40
  - نَظَرِيَّة مَقَاس theory3 2
بَيَانَات:
  - obs 7 40
  - obs 5 28
  - obs 9 52
  - obs 11 64
  - obs 1 4
قَانُون:
  - قَانُون نَظَرِيَّة كَانَ lossless iff هُوَ تَنَبَّأَ كُلّ رَصْد بِالضَّبْط
  - قَانُون اِخْتَارَ الـ lossless نَظَرِيَّة مِنْ أَقَلَّ مَقَاس
عِلْم اَلْمَعَانِي: شَكَّلَ linear y = p1 * x + p2؛ شَكَّلَ square y = x * x + p2؛ شَكَّلَ constant y = p2؛ شَكَّلَ الـ طَاوِلَة y = entry(x).
smallest lossless نَظَرِيَّة مَاذَا؟

Კანდიდატები:
  - სასათაურო სიტყვა: theory1, 11 და 64
  - სასათაურო სიტყვა: theory1, 1 და 4
  - თეორია: theory0, linear, 8 და 0
  - სასათაურო სიტყვა: theory1, 9 და 52
  - theory2 3 თეორია ზომა
  - theory1 10 თეორია ზომა
  - theory0 3 თეორია ზომა
  - თეორია: theory2, linear, 6 და -2
  - თეორია: theory1, მაგიდა, 0 და 0
  - სასათაურო სიტყვა: theory1, 5 და 28
  - თეორია: theory3, square, 6 და -6
  - სასათაურო სიტყვა: theory1, 7 და 40
  - theory3 2 თეორია ზომა
Მონაცემები:
  - 7 40 obs
  - 5 28 obs
  - 9 52 obs
  - 11 64 obs
  - 1 4 obs
Წესი:
  - წესი თეორია ყოფნა უდანაკარგო iff ის predict ყველა დაკვირვება ზუსტად
  - წესი ამორჩევა უდანაკარგო თეორია of least ზომა
Სემანტიკა: linear y = p1 * x + p2 ბლანკი; square y = x * x + p2 ბლანკი; constant y = p2 ბლანკი; მაგიდა y = entry(x) ბლანკი.
Smallest უდანაკარგო თეორია რა?

Kaiwhakauru:
  - tāurunga: theory1, 11 me 64
  - tāurunga: theory1, 1 me 4
  - ariā: theory0, linear, 8 me 0
  - tāurunga: theory1, 9 me 52
  - ariā size theory2 3
  - ariā size theory1 10
  - ariā size theory0 3
  - ariā: theory2, linear, 6 me -2
  - ariā: theory1, tēpu, 0 me 0
  - tāurunga: theory1, 5 me 28
  - ariā: theory3, square, 6 me -6
  - tāurunga: theory1, 7 me 40
  - ariā size theory3 2
Hōtuku:
  - obs 7 40
  - obs 5 28
  - obs 9 52
  - obs 11 64
  - obs 1 4
Rekureihana:
  - rekureihana ariā is lossless iff it matakite every observation pū
  - rekureihana whiri te lossless ariā o least size
Semantics: āhua linear y = p1 * x + p2; āhua square y = x * x + p2; āhua constant y = p2; āhua te tēpu y = entry(x).
Smallest lossless ariā unutai?

Candidates:
  - mục từ: theory1, 11 và 64
  - mục từ: theory1, 1 và 4
  - lý thuyết: theory0, linear, 8 và 0
  - mục từ: theory1, 9 và 52
  - theory2 lý thuyết kích thước 3
  - theory1 lý thuyết kích thước 10
  - theory0 lý thuyết kích thước 3
  - lý thuyết: theory2, linear, 6 và -2
  - lý thuyết: theory1, bàn, 0 và 0
  - mục từ: theory1, 5 và 28
  - lý thuyết: theory3, square, 6 và -6
  - mục từ: theory1, 7 và 40
  - theory3 lý thuyết kích thước 2
Dữ liệu:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Quy tắc:
  - quy tắc lý thuyết được lossless iff nó dự báo mỗi observation đúng rồi
  - quy tắc chọn the lossless lý thuyết bằng least kích thước
Ngữ nghĩa: linear làm thành y = p1 * x + p2; square làm thành y = x * x + p2; constant làm thành y = p2; bàn làm thành y = entry(x).
Smallest lossless lý thuyết gì?

ผู้สมัคร:
  - entry:theory1, 11และ64
  - entry:theory1, 1และ4
  - ทฤษฎี:theory0, linear, 8และ0
  - entry:theory1, 9และ52
  - theory2ทฤษฎีขนาด3
  - theory1ทฤษฎีขนาด10
  - theory0ทฤษฎีขนาด3
  - ทฤษฎี:theory2, linear, 6และ-2
  - ทฤษฎี:theory1, โต๊ะ, 0และ0
  - entry:theory1, 5และ28
  - ทฤษฎี:theory3, square, 6และ-6
  - entry:theory1, 7และ40
  - theory3ทฤษฎีขนาด2
ข้อมูล:
  - 7obs40
  - 5obs28
  - 9obs52
  - 11obs64
  - 1obs4
กฎ:กฎ:ทฤษฎีถูกlosslessiffมันทำนายทุกการสังเกตexactly; กฎ:เลือกlosslessทฤษฎีของleastขนาด.
อรรถศาสตร์:linearรูปร่างy = p1 * x + p2; squareรูปร่างy = x * x + p2; constantรูปร่างy = p2; โต๊ะรูปร่างy = entry(x).
smallestlosslessทฤษฎีอะไร?

வேட்பாளர்:
  - உள்நுழைவதற்கு அனுமதி: theory1, 11 மற்றும் 64
  - உள்நுழைவதற்கு அனுமதி: theory1, 1 மற்றும் 4
  - theory: theory0, linear, 8 மற்றும் 0
  - உள்நுழைவதற்கு அனுமதி: theory1, 9 மற்றும் 52
  - theory2 3 theory size
  - theory1 10 theory size
  - theory0 3 theory size
  - theory: theory2, linear, 6 மற்றும் -2
  - theory: theory1, மேசை, 0 மற்றும் 0
  - உள்நுழைவதற்கு அனுமதி: theory1, 5 மற்றும் 28
  - theory: theory3, square, 6 மற்றும் -6
  - உள்நுழைவதற்கு அனுமதி: theory1, 7 மற்றும் 40
  - theory3 2 theory size
தரவுகள்:
  - 7 40 obs
  - 5 28 obs
  - 9 52 obs
  - 11 64 obs
  - 1 4 obs
rules: rule theory படு lossless iff it கணி ஒவ்வொரு observation exactly; rule choose lossless theory கொண்ட least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; மேசை y = entry(x) form.
smallest lossless theory என்ன?

Wagombea ni:
  - entry: theory1, 11 na 64
  - entry: theory1, 1 na 4
  - theory: theory0, linear, 8 na 0
  - entry: theory1, 9 na 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 na -2
  - theory: theory1, meza, 0 na 0
  - entry: theory1, 5 na 28
  - theory: theory3, square, 6 na -6
  - entry: theory1, 7 na 40
  - theory3 theory size 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

Candidates:
  - entry: theory1, 11 dóó 64
  - entry: theory1, 1 dóó 4
  - theory: theory0, linear, 8 dóó 0
  - entry: theory1, 9 dóó 52
  - theory2 3 theory size
  - theory1 10 theory size
  - theory0 3 theory size
  - theory: theory2, linear, 6 dóó -2
  - theory: theory1, bikááʼ adání, 0 dóó 0
  - entry: theory1, 5 dóó 28
  - theory: theory3, square, 6 dóó -6
  - entry: theory1, 7 dóó 40
  - theory3 2 theory size
Data:
  - 7 40 obs
  - 5 28 obs
  - 9 52 obs
  - 11 64 obs
  - 1 4 obs
Bee hazʼáanii:
  - bee hazʼáanii theory átʼé lossless iff it predict every observation exactly
  - bee hazʼáanii choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; bikááʼ adání y = entry(x) form.
Smallest lossless theory haʼátʼíísh?

Candidates:
  - entry: theory1, 11 aamma 64
  - entry: theory1, 1 aamma 4
  - theory: theory0, linear, 8 aamma 0
  - entry: theory1, 9 aamma 52
  - theory2 3 theory size
  - theory1 10 theory size
  - theory0 3 theory size
  - theory: theory2, linear, 6 aamma -2
  - theory: theory1, table, 0 aamma 0
  - entry: theory1, 5 aamma 28
  - theory: theory3, square, 6 aamma -6
  - entry: theory1, 7 aamma 40
  - theory3 2 theory size
Data:
  - 7 40 obs
  - 5 28 obs
  - 9 52 obs
  - 11 64 obs
  - 1 4 obs
Rules: rule theory a lossless iff una predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 blanketti; square y = x * x + p2 blanketti; constant y = p2 blanketti; table y = entry(x) blanketti.
Smallest lossless theory what?

Candidates:
  - entry: theory1, 11 na 64
  - entry: theory1, 1 na 4
  - theory: theory0, linear, 8 na 0
  - entry: theory1, 9 na 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 na -2
  - theory: theory1, table, 0 na 0
  - entry: theory1, 5 na 28
  - theory: theory3, square, 6 na -6
  - entry: theory1, 7 na 40
  - theory3 theory size 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory bilong least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory1, 11 64
  - entry: theory1, 1 4
  - theory: theory0, linear, 8 0
  - entry: theory1, 9 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 -2
  - theory: theory1, table, 0 0
  - entry: theory1, 5 28
  - theory: theory3, square, 6 -6
  - entry: theory1, 7 40
  - theory3 theory size 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Nikanixi:
  - nikanixi theory is lossless iff it predict every observation exactly
  - nikanixi choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory kwèch?

Candidates:
  - entry: theory1, 11 а 64
  - entry: theory1, 1 а 4
  - theory: theory0, linear, 8 а 0
  - entry: theory1, 9 а 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 а -2
  - theory: theory1, table, 0 а 0
  - entry: theory1, 5 а 28
  - theory: theory3, square, 6 а -6
  - entry: theory1, 7 а 40
  - theory3 theory size 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Rules:
  - rule theory хила lossless iff it predict дерриг observation exactly
  - rule хержа lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory фу?

후보자:
  - 항목: theory1, 11 64
  - 항목: theory1, 1 4
  - 이론: theory0, linear, 8 0
  - 항목: theory1, 9 52
  - theory2 3 이론 크기
  - theory1 10 이론 크기
  - theory0 3 이론 크기
  - 이론: theory2, linear, 6 -2
  - 이론: theory1, 테이블, 0 0
  - 항목: theory1, 5 28
  - 이론: theory3, square, 6 -6
  - 항목: theory1, 7 40
  - theory3 2 이론 크기
자료:
  - 7 40 obs
  - 5 28 obs
  - 9 52 obs
  - 11 64 obs
  - 1 4 obs
규칙: 규칙 이론 is lossless iff 이것 예언하다 각 관찰 정확하게; 규칙 고르다 lossless 이론...의 가장 적게 크기.
의미론: linear y = p1 * x + p2 형상; square y = x * x + p2 형상; constant y = p2 형상; 테이블 y = entry(x) 형상.
smallest lossless 이론 무엇?

Kandidatu:
  - sarrera: theory1, 11 eta 64
  - sarrera: theory1, 1 eta 4
  - theory: theory0, linear, 8 eta 0
  - sarrera: theory1, 9 eta 52
  - theory2 3 theory tamaina
  - theory1 10 theory tamaina
  - theory0 3 theory tamaina
  - theory: theory2, linear, 6 eta -2
  - theory: theory1, mahai, 0 eta 0
  - sarrera: theory1, 5 eta 28
  - theory: theory3, square, 6 eta -6
  - sarrera: theory1, 7 eta 40
  - theory3 2 theory tamaina
Data:
  - 7 40 obs
  - 5 28 obs
  - 9 52 obs
  - 11 64 obs
  - 1 4 obs
Arau:
  - arau bat theory izan lossless iff it aurresan every observation exactly
  - arau aukeratu the lossless theory of least tamaina
Semantics: linear y = p1 * x + p2 forma; square y = x * x + p2 forma; constant y = p2 forma; mahai y = entry(x) forma.
Smallest lossless theory zer?

ᎠᏙᎩᏯᏍᎩ:
  - entry: theory1, 11 ᎠᎴ 64
  - entry: theory1, 1 ᎠᎴ 4
  - theory: theory0, linear, 8 ᎠᎴ 0
  - entry: theory1, 9 ᎠᎴ 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 ᎠᎴ -2
  - theory: theory1, ᎦᏍᎩᎶ, 0 ᎠᎴ 0
  - entry: theory1, 5 ᎠᎴ 28
  - theory: theory3, square, 6 ᎠᎴ -6
  - entry: theory1, 7 ᎠᎴ 40
  - theory3 theory size 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ᎦᏍᎩᎶ form y = entry(x).
What smallest lossless theory?

Candidates:
  - entry: theory1, 11 64
  - entry: theory1, 1 4
  - theory: theory0, linear, 8 0
  - entry: theory1, 9 52
  - theory2 theory chhika 3
  - theory1 theory chhika 10
  - theory0 theory chhika 3
  - theory: theory2, linear, 6 -2
  - theory: theory1, patacha, 0 0
  - entry: theory1, 5 28
  - theory: theory3, square, 6 -6
  - entry: theory1, 7 40
  - theory3 theory chhika 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Rules:
  - rule theory tiyay lossless iff it predict tukuy observation exactly
  - rule akllay lossless theory of least chhika
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; patacha form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory1, 11 ыкӏи 64
  - entry: theory1, 1 ыкӏи 4
  - тиориэ: theory0, linear, 8 ыкӏи 0
  - entry: theory1, 9 ыкӏи 52
  - theory2 3 тиориэ size
  - theory1 10 тиориэ size
  - theory0 3 тиориэ size
  - тиориэ: theory2, linear, 6 ыкӏи -2
  - тиориэ: theory1, table, 0 ыкӏи 0
  - entry: theory1, 5 ыкӏи 28
  - тиориэ: theory3, square, 6 ыкӏи -6
  - entry: theory1, 7 ыкӏи 40
  - theory3 2 тиориэ size
Data:
  - 7 40 obs
  - 5 28 obs
  - 9 52 obs
  - 11 64 obs
  - 1 4 obs
Rules: rule тиориэ is lossless iff it predict every observation exactly; rule choose the lossless тиориэ of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless тиориэ сыд?

Candidates:
  - entry: theory1, 11 thiab 64
  - entry: theory1, 1 thiab 4
  - theory: theory0, linear, 8 thiab 0
  - entry: theory1, 9 thiab 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 thiab -2
  - theory: theory1, rooj, 0 thiab 0
  - entry: theory1, 5 thiab 28
  - theory: theory3, square, 6 thiab -6
  - entry: theory1, 7 thiab 40
  - theory3 theory size 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Cai: cai theory is lossless iff nws predict every observation exactly; cai choose lossless theory of least size.
Lub ntsiab: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; rooj form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory1, 11 64
  - entry: theory1, 1 4
  - theory: theory0, linear, 8 0
  - entry: theory1, 9 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 -2
  - theory: theory1, table, 0 0
  - entry: theory1, 5 28
  - theory: theory3, square, 6 -6
  - entry: theory1, 7 40
  - theory3 theory size 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of wy krook size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory ining-jak?

Candidates:
  - entry: theory1, 11 micha' 64
  - entry: theory1, 1 micha' 4
  - theory: theory0, linear, 8 micha' 0
  - entry: theory1, 9 micha' 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 micha' -2
  - theory: theory1, table, 0 micha' 0
  - entry: theory1, 5 micha' 28
  - theory: theory3, square, 6 micha' -6
  - entry: theory1, 7 micha' 40
  - theory3 theory size 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory nanta?

Candidates:
  - entry: theory1, 11 カ 64
  - entry: theory1, 1 カ 4
  - theory: theory0, linear, 8 カ 0
  - entry: theory1, 9 カ 52
  - theory2 3 theory size
  - theory1 10 theory size
  - theory0 3 theory size
  - theory: theory2, linear, 6 カ -2
  - theory: theory1, table, 0 カ 0
  - entry: theory1, 5 カ 28
  - theory: theory3, square, 6 カ -6
  - entry: theory1, 7 カ 40
  - theory3 2 theory size
Data:
  - 7 40 obs
  - 5 28 obs
  - 9 52 obs
  - 11 64 obs
  - 1 4 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 ノカ; square y = x * x + p2 ノカ; constant y = p2 ノカ; table y = entry(x) ノカ.
Smallest lossless theory what?

Candidates:
  - entry: theory1, 11 ынкъам 64
  - entry: theory1, 1 ынкъам 4
  - theory: theory0, linear, 8 ынкъам 0
  - entry: theory1, 9 ынкъам 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 ынкъам -2
  - theory: theory1, table, 0 ынкъам 0
  - entry: theory1, 5 ынкъам 28
  - theory: theory3, square, 6 ынкъам -6
  - entry: theory1, 7 ынкъам 40
  - theory3 theory size 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory1, 11 yéetel 64
  - entry: theory1, 1 yéetel 4
  - theory: theory0, linear, 8 yéetel 0
  - entry: theory1, 9 yéetel 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 yéetel -2
  - theory: theory1, table, 0 yéetel 0
  - entry: theory1, 5 yéetel 28
  - theory: theory3, square, 6 yéetel -6
  - entry: theory1, 7 yéetel 40
  - theory3 theory size 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Rules:
  - rule theory yan lossless iff it predict every observation exactly
  - rule yéey lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory1, 11 64
  - entry: theory1, 1 4
  - theory: theory0, linear, 8 0
  - entry: theory1, 9 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 -2
  - theory: theory1, mę́soną, 0 0
  - entry: theory1, 5 28
  - theory: theory3, square, 6 -6
  - entry: theory1, 7 40
  - theory3 theory size 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Rules:
  - rule theory is lossless iff ą́wąną predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mę́soną form y = entry(x).
Smallest lossless theory híli?

Candidates:
  - entry: theory1, 11 na 64
  - entry: theory1, 1 na 4
  - theory: theory0, linear, 8 na 0
  - entry: theory1, 9 na 52
  - theory2 3 theory size
  - theory1 10 theory size
  - theory0 3 theory size
  - theory: theory2, linear, 6 na -2
  - theory: theory1, table, 0 na 0
  - entry: theory1, 5 na 28
  - theory: theory3, square, 6 na -6
  - entry: theory1, 7 na 40
  - theory3 2 theory size
Data:
  - 7 40 obs
  - 5 28 obs
  - 9 52 obs
  - 11 64 obs
  - 1 4 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory1, 11 64
  - entry: theory1, 1 4
  - theory: theory0, linear, 8 0
  - entry: theory1, 9 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 -2
  - theory: theory1, table, 0 0
  - entry: theory1, 5 28
  - theory: theory3, square, 6 -6
  - entry: theory1, 7 40
  - theory3 theory size 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory1, 11 64
  - entry: theory1, 1 4
  - theory: theory0, linear, 8 0
  - entry: theory1, 9 52
  - theory2 3 theory size
  - theory1 10 theory size
  - theory0 3 theory size
  - theory: theory2, linear, 6 -2
  - theory: theory1, table, 0 0
  - entry: theory1, 5 28
  - theory: theory3, square, 6 -6
  - entry: theory1, 7 40
  - theory3 2 theory size
Data:
  - 7 40 obs
  - 5 28 obs
  - 9 52 obs
  - 11 64 obs
  - 1 4 obs
Rules:
  - rule maya theory is lossless iff it predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory1, 11 ǂʻá 64
  - entry: theory1, 1 ǂʻá 4
  - theory: theory0, linear, 8 ǂʻá 0
  - entry: theory1, 9 ǂʻá 52
  - theory2 theory ʻǁnàhã 3
  - theory1 theory ʻǁnàhã 10
  - theory0 theory ʻǁnàhã 3
  - theory: theory2, linear, 6 ǂʻá -2
  - theory: theory1, table, 0 ǂʻá 0
  - entry: theory1, 5 ǂʻá 28
  - theory: theory3, square, 6 ǂʻá -6
  - entry: theory1, 7 ǂʻá 40
  - theory3 theory ʻǁnàhã 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Rules:
  - rule theory ǀîi lossless iff èh predict every observation exactly
  - rule choose lossless theory of least ʻǁnàhã
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory1, 11 64
  - entry: theory1, 1 4
  - theory: theory0, linear, 8 0
  - entry: theory1, 9 52
  - theory2 3 theory size
  - theory1 10 theory size
  - theory0 3 theory size
  - theory: theory2, linear, 6 -2
  - theory: theory1, остол, 0 0
  - entry: theory1, 5 28
  - theory: theory3, square, 6 -6
  - entry: theory1, 7 40
  - theory3 2 theory size
Data:
  - 7 40 obs
  - 5 28 obs
  - 9 52 obs
  - 11 64 obs
  - 1 4 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; остол y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory1, 11 64
  - entry: theory1, 1 4
  - theory: theory0, linear, 8 0
  - entry: theory1, 9 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 -2
  - theory: theory1, table, 0 0
  - entry: theory1, 5 28
  - theory: theory3, square, 6 -6
  - entry: theory1, 7 40
  - theory3 theory size 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory1, 11 64
  - entry: theory1, 1 4
  - theory: theory0, linear, 8 0
  - entry: theory1, 9 52
  - theory2 3 theory size
  - theory1 10 theory size
  - theory0 3 theory size
  - theory: theory2, linear, 6 -2
  - theory: theory1, table, 0 0
  - entry: theory1, 5 28
  - theory: theory3, square, 6 -6
  - entry: theory1, 7 40
  - theory3 2 theory size
Data:
  - 7 40 obs
  - 5 28 obs
  - 9 52 obs
  - 11 64 obs
  - 1 4 obs
Rules:
  - rule theory is lossless iff kitu predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory1, 11 64
  - entry: theory1, 1 4
  - theory: theory0, linear, 8 0
  - entry: theory1, 9 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 -2
  - theory: theory1, mesa, 0 0
  - entry: theory1, 5 28
  - theory: theory3, square, 6 -6
  - entry: theory1, 7 40
  - theory3 theory size 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mesa form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory1, 11 64
  - entry: theory1, 1 4
  - theory: theory0, linear, 8 0
  - entry: theory1, 9 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 -2
  - theory: theory1, table, 0 0
  - entry: theory1, 5 28
  - theory: theory3, square, 6 -6
  - entry: theory1, 7 40
  - theory3 theory size 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Rules:
  - rule theory nemi lossless iff yaja predict every observation exactly
  - rule choose ne lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ne table form y = entry(x).
Smallest lossless theory tay?

Les candidats sont:
  - article: theory1, 11 et 64
  - article: theory1, 1 et 4
  - théorie: theory0, linear, 8 et 0
  - article: theory1, 9 et 52
  - theory2 théorie taille 3
  - theory1 théorie taille 10
  - theory0 théorie taille 3
  - théorie: theory2, linear, 6 et -2
  - théorie: theory1, table, 0 et 0
  - article: theory1, 5 et 28
  - théorie: theory3, square, 6 et -6
  - article: theory1, 7 et 40
  - theory3 théorie taille 2
Les données sont:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Les règles sont:
  - règle un théorie être lossless ssi il prédire tout observation exactement
  - règle choisir le lossless théorie du moindre taille
La sémantique est : linear former y = p1 * x + p2 ; square former y = x * x + p2 ; constant former y = p2 ; la table former y = entry(x).
Quoi smallest lossless théorie ?

Kandidato:
  - entry: theory1, 11 kaj 64
  - entry: theory1, 1 kaj 4
  - teorio: theory0, linear, 8 kaj 0
  - entry: theory1, 9 kaj 52
  - theory2 teorio grandeco 3
  - theory1 teorio grandeco 10
  - theory0 teorio grandeco 3
  - teorio: theory2, linear, 6 kaj -2
  - teorio: theory1, tablo, 0 kaj 0
  - entry: theory1, 5 kaj 28
  - teorio: theory3, square, 6 kaj -6
  - entry: theory1, 7 kaj 40
  - theory3 teorio grandeco 2
Datumo:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Regulo: regulo teorio egali lossless iff ĝi predict ĉiu observo ekzakte; regulo elekti lossless teorio de plej malmulta grandeco.
Semantics: linear formi y = p1 * x + p2; square formi y = x * x + p2; constant formi y = p2; tablo formi y = entry(x).
Smallest lossless teorio kio?

Indulók:
  - szócikk: theory1, 11 és 64
  - szócikk: theory1, 1 és 4
  - elmélet: theory0, linear, 8 és 0
  - szócikk: theory1, 9 és 52
  - theory2 elmélet méret 3
  - theory1 elmélet méret 10
  - theory0 elmélet méret 3
  - elmélet: theory2, linear, 6 és -2
  - elmélet: theory1, asztal, 0 és 0
  - szócikk: theory1, 5 és 28
  - elmélet: theory3, square, 6 és -6
  - szócikk: theory1, 7 és 40
  - theory3 elmélet méret 2
Adat:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Szabályok:
  - szabály elmélet van veszteségmentes acsa az megjósol minden megfigyelés pontosan
  - szabály kiválaszt a veszteségmentes elmélet of legkisebb méret
Szemantika: linear kialakít y = p1 * x + p2; square kialakít y = x * x + p2; constant kialakít y = p2; a asztal kialakít y = entry(x).
Smallest veszteségmentes elmélet melyik?

候選人:
  - entry:theory1, 11及64
  - entry:theory1, 1及4
  - theory:theory0, linear, 8及0
  - entry:theory1, 9及52
  - theory2theory size3
  - theory1theory size10
  - theory0theory size3
  - theory:theory2, linear, 6及-2
  - theory:theory1, 檯, 0及0
  - entry:theory1, 5及28
  - theory:theory3, square, 6及-6
  - entry:theory1, 7及40
  - theory3theory size2
數據:
  - 7obs40
  - 5obs28
  - 9obs52
  - 11obs64
  - 1obs4
rules:rule:一theory是losslessiffitpredict每observationexactly; rule:揀losslesstheory...嘅leastsize.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; 檯formy = entry(x).
smallest lossless theory乜嘢?

Candidates:
  - entry: theory1, 11 とぅ 64
  - entry: theory1, 1 とぅ 4
  - theory: theory0, linear, 8 とぅ 0
  - entry: theory1, 9 とぅ 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 とぅ -2
  - theory: theory1, table, 0 とぅ 0
  - entry: theory1, 5 とぅ 28
  - theory: theory3, square, 6 とぅ -6
  - entry: theory1, 7 とぅ 40
  - theory3 theory size 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Rules: rule theory 有ん lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Үміткер:
  - entry: theory1, 11 және 64
  - entry: theory1, 1 және 4
  - теория: theory0, linear, 8 және 0
  - entry: theory1, 9 және 52
  - theory2 теория мөлшер 3
  - theory1 теория мөлшер 10
  - theory0 теория мөлшер 3
  - теория: theory2, linear, 6 және -2
  - теория: theory1, үстел, 0 және 0
  - entry: theory1, 5 және 28
  - теория: theory3, square, 6 және -6
  - entry: theory1, 7 және 40
  - theory3 теория мөлшер 2
Деректер:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Ереже: ереже теория is lossless iff ол predict әр бақылау exactly; ереже таңдау lossless теория туралы least мөлшер.
Семантикалық: linear пішін y = p1 * x + p2; square пішін y = x * x + p2; constant пішін y = p2; үстел пішін y = entry(x).
Smallest lossless теория не?

מועמדת:
  - entry: theory1, 11 וְ־ 64
  - entry: theory1, 1 וְ־ 4
  - תּוֹרָה: theory0, linear, 8 וְ־ 0
  - entry: theory1, 9 וְ־ 52
  - theory2 תּוֹרָה גֹּדֶל 3
  - theory1 תּוֹרָה גֹּדֶל 10
  - theory0 תּוֹרָה גֹּדֶל 3
  - תּוֹרָה: theory2, linear, 6 וְ־ -2
  - תּוֹרָה: theory1, טַבְלָה, 0 וְ־ 0
  - entry: theory1, 5 וְ־ 28
  - תּוֹרָה: theory3, square, 6 וְ־ -6
  - entry: theory1, 7 וְ־ 40
  - theory3 תּוֹרָה גֹּדֶל 2
נְתוּנִים:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
מָשַׁל:
  - מָשַׁל אַחַת תּוֹרָה הוא lossless אםם זֶה predict כֹּל תַּצְפִּית בדיוק
  - מָשַׁל בחר ה־ lossless תּוֹרָה שֶׁל least גֹּדֶל
תורת המשמעים: linear צורה y = p1 * x + p2; square צורה y = x * x + p2; constant צורה y = p2; טַבְלָה ה־ צורה y = entry(x).
איזה smallest lossless תּוֹרָה?

Candidates:
  - entry: theory1, 11 დო 64
  - entry: theory1, 1 დო 4
  - theory: theory0, linear, 8 დო 0
  - entry: theory1, 9 დო 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 დო -2
  - theory: theory1, table, 0 დო 0
  - entry: theory1, 5 დო 28
  - theory: theory3, square, 6 დო -6
  - entry: theory1, 7 დო 40
  - theory3 theory size 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Kandidat:
  - lema: theory1, 11 dan 64
  - lema: theory1, 1 dan 4
  - teori: theory0, linear, 8 dan 0
  - lema: theory1, 9 dan 52
  - theory2 teori ukuran 3
  - theory1 teori ukuran 10
  - theory0 teori ukuran 3
  - teori: theory2, linear, 6 dan -2
  - teori: theory1, meja, 0 dan 0
  - lema: theory1, 5 dan 28
  - teori: theory3, square, 6 dan -6
  - lema: theory1, 7 dan 40
  - theory3 teori ukuran 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Rules:
  - rule teori berada lossless iff it predict setiap observation tepat
  - rule memilih si lossless teori dari least ukuran
Semantik: linear formulir y = p1 * x + p2; square formulir y = x * x + p2; constant formulir y = p2; meja si formulir y = entry(x).
Smallest lossless teori apa?

បេក្ខជន:
  - មេពាក្យ:theory1, 11នឹង64
  - មេពាក្យ:theory1, 1នឹង4
  - ទ្រឹស្ដី:theory0, linear, 8នឹង0
  - មេពាក្យ:theory1, 9នឹង52
  - theory2ទ្រឹស្ដីទំហំ3
  - theory1ទ្រឹស្ដីទំហំ10
  - theory0ទ្រឹស្ដីទំហំ3
  - ទ្រឹស្ដី:theory2, linear, 6នឹង-2
  - ទ្រឹស្ដី:theory1, តុ, 0នឹង0
  - មេពាក្យ:theory1, 5នឹង28
  - ទ្រឹស្ដី:theory3, square, 6នឹង-6
  - មេពាក្យ:theory1, 7នឹង40
  - theory3ទ្រឹស្ដីទំហំ2
ទិន្នន័យ:
  - 7obs40
  - 5obs28
  - 9obs52
  - 11obs64
  - 1obs4
ក្បួន:ក្បួន:ទ្រឹស្ដីត្រូវបានlosslessiffវាចាប់យាមរាល់គំនន់exactly; ក្បួន:រើសthelosslessទ្រឹស្ដីនៃleastទំហំ.
និឃណ្ដសាស្ត្រ:linearគ្រោងy = p1 * x + p2; squareគ្រោងy = x * x + p2; constantគ្រោងy = p2; តុគ្រោងy = entry(x).
smallestlosslessទ្រឹស្ដីអី?

ຜູ້ສະໝັກ:
  - entry:theory1, 11ແລະ64
  - entry:theory1, 1ແລະ4
  - ທິດສະດີ:theory0, linear, 8ແລະ0
  - entry:theory1, 9ແລະ52
  - theory2ທິດສະດີຂະຫນາດ3
  - theory1ທິດສະດີຂະຫນາດ10
  - theory0ທິດສະດີຂະຫນາດ3
  - ທິດສະດີ:theory2, linear, 6ແລະ-2
  - ທິດສະດີ:theory1, ໂຕະ, 0ແລະ0
  - entry:theory1, 5ແລະ28
  - ທິດສະດີ:theory3, square, 6ແລະ-6
  - entry:theory1, 7ແລະ40
  - theory3ທິດສະດີຂະຫນາດ2
ຂໍ້ມູນ:
  - 7obs40
  - 5obs28
  - 9obs52
  - 11obs64
  - 1obs4
ກະຕິກາ:ກະຕິກາ:ທິດສະດີຢູ່losslessiffມັນທຳນວາຍທຸກobservationexactly; ກະຕິກາ:ເລືອກlosslessທິດສະດີຂອງleastຂະຫນາດ.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; ໂຕະformy = entry(x).
smallestlosslessທິດສະດີຫຍັງ?

candidates:
  - entry: theory1, 11 మరియు 64
  - entry: theory1, 1 మరియు 4
  - theory: theory0, linear, 8 మరియు 0
  - entry: theory1, 9 మరియు 52
  - theory2 3 theory size
  - theory1 10 theory size
  - theory0 3 theory size
  - theory: theory2, linear, 6 మరియు -2
  - theory: theory1, బల్ల, 0 మరియు 0
  - entry: theory1, 5 మరియు 28
  - theory: theory3, square, 6 మరియు -6
  - entry: theory1, 7 మరియు 40
  - theory3 2 theory size
data:
  - 7 40 obs
  - 5 28 obs
  - 9 52 obs
  - 11 64 obs
  - 1 4 obs
నియమం: నియమం theory ఉండు lossless iff it predict ప్రతి పరిశీలన exactly; నియమం choose lossless theory of least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; బల్ల y = entry(x) form.
smallest lossless theory ఏమిటి?

Candidates:
  - entry: theory1, 11 64
  - entry: theory1, 1 4
  - theory: theory0, linear, 8 0
  - entry: theory1, 9 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 -2
  - theory: theory1, table, 0 0
  - entry: theory1, 5 28
  - theory: theory3, square, 6 -6
  - entry: theory1, 7 40
  - theory3 theory size 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Rules: rule theory wà lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
What smallest lossless theory?

Candidates:
  - entry: theory1, 11 64
  - entry: theory1, 1 4
  - theory: theory0, linear, 8 0
  - entry: theory1, 9 52
  - theory2 3 theory size
  - theory1 10 theory size
  - theory0 3 theory size
  - theory: theory2, linear, 6 -2
  - theory: theory1, table, 0 0
  - entry: theory1, 5 28
  - theory: theory3, square, 6 -6
  - entry: theory1, 7 40
  - theory3 2 theory size
Data:
  - 7 40 obs
  - 5 28 obs
  - 9 52 obs
  - 11 64 obs
  - 1 4 obs
Rules:
  - rule theory naiágúóli lossless iff it predict every observation exactly
  - rule choose the lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

candidates:
  - entry: theory1, 11 64
  - entry: theory1, 1 4
  - theory: theory0, linear, 8 0
  - entry: theory1, 9 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 -2
  - theory: theory1, table, 0 0
  - entry: theory1, 5 28
  - theory: theory3, square, 6 -6
  - entry: theory1, 7 40
  - theory3 theory size 2
data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
smallest lossless theory what?

Candidates:
  - entry: theory1, 11 64
  - entry: theory1, 1 4
  - theory: theory0, linear, 8 0
  - entry: theory1, 9 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 -2
  - theory: theory1, tafra, 0 0
  - entry: theory1, 5 28
  - theory: theory3, square, 6 -6
  - entry: theory1, 7 40
  - theory3 theory size 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; tafra form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory1, 11 64
  - entry: theory1, 1 4
  - theory: theory0, linear, 8 0
  - entry: theory1, 9 52
  - theory2 theory size 3
  - theory1 theory size 10
  - theory0 theory size 3
  - theory: theory2, linear, 6 -2
  - theory: theory1, táxemésėhestȯtse, 0 0
  - entry: theory1, 5 28
  - theory: theory3, square, 6 -6
  - entry: theory1, 7 40
  - theory3 theory size 2
Data:
  - 7 obs 40
  - 5 obs 28
  - 9 obs 52
  - 11 obs 64
  - 1 obs 4
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; táxemésėhestȯtse form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory1, 11 64
  - entry: theory1, 1 4
  - theory: theory0, linear, 8 0
  - entry: theory1, 9 52
  - theory2 3 theory size
  - theory1 10 theory size
  - theory0 3 theory size
  - theory: theory2, linear, 6 -2
  - theory: theory1, ствал, 0 0
  - entry: theory1, 5 28
  - theory: theory3, square, 6 -6
  - entry: theory1, 7 40
  - theory3 2 theory size
Data:
  - 7 40 obs
  - 5 28 obs
  - 9 52 obs
  - 11 64 obs
  - 1 4 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; ствал y = entry(x) form.
Smallest lossless theory вуч?

The candidates are:
  - theory0 theory size 10
  - theory: theory0, table, 0 and 0
  - entry: theory0, 2 and 5
  - entry: theory0, 11 and 41
  - theory3 theory size 3
  - theory: theory1, square, 2 and -6
  - theory2 theory size 3
  - entry: theory0, 1 and 1
  - entry: theory0, 6 and 21
  - theory: theory3, linear, 6 and -1
  - entry: theory0, 7 and 25
  - theory: theory2, linear, 4 and -3
  - theory1 theory size 2
The data are:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

Los candidatos son:
  - theory0 el tamaño de la teoría 10
  - la teoría: theory0, mesa, 0 y 0
  - la entrada: theory0, 2 y 5
  - la entrada: theory0, 11 y 41
  - theory3 el tamaño de la teoría 3
  - la teoría: theory1, square, 2 y -6
  - theory2 el tamaño de la teoría 3
  - la entrada: theory0, 1 y 1
  - la entrada: theory0, 6 y 21
  - la teoría: theory3, linear, 6 y -1
  - la entrada: theory0, 7 y 25
  - la teoría: theory2, linear, 4 y -3
  - theory1 el tamaño de la teoría 2
Los datos son:
  - 1 la observación 1
  - 2 la observación 5
  - 11 la observación 41
  - 6 la observación 21
  - 7 la observación 25
Las reglas son:
  - la regla: a la teoría es lossless si y sólo si it predice every observation exactamente
  - la regla: choose el lossless la teoría de least tamaño
La semántica es: linear la forma y = p1 * x + p2; square la forma y = x * x + p2; constant la forma y = p2; la mesa la forma y = entry(x).
¿Qué smallest lossless la teoría?

候选项如下：
  - theory0的理论规模是10
  - 的理论是：theory0、桌子、0和0
  - 的条目是：theory0、2和5
  - 的条目是：theory0、11和41
  - theory3的理论规模是3
  - 的理论是：theory1、square、2和-6
  - theory2的理论规模是3
  - 的条目是：theory0、1和1
  - 的条目是：theory0、6和21
  - 的理论是：theory3、linear、6和-1
  - 的条目是：theory0、7和25
  - 的理论是：theory2、linear、4和-3
  - theory1的理论规模是2
数据如下：
  - 1观察到1
  - 2观察到5
  - 11观察到41
  - 6观察到21
  - 7观察到25
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

Adaylar:
  - theory0 10 kuram boyut
  - kuram: theory0, masa, 0 ve 0
  - entry: theory0, 2 ve 5
  - entry: theory0, 11 ve 41
  - theory3 3 kuram boyut
  - kuram: theory1, square, 2 ve -6
  - theory2 3 kuram boyut
  - entry: theory0, 1 ve 1
  - entry: theory0, 6 ve 21
  - kuram: theory3, linear, 6 ve -1
  - entry: theory0, 7 ve 25
  - kuram: theory2, linear, 4 ve -3
  - theory1 2 kuram boyut
Veriler:
  - 1 1 obs
  - 2 5 obs
  - 11 41 obs
  - 6 21 obs
  - 7 25 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

Wagombea ni:
  - theory0 theory size 10
  - theory: theory0, meza, 0 na 0
  - entry: theory0, 2 na 5
  - entry: theory0, 11 na 41
  - theory3 theory size 3
  - theory: theory1, square, 2 na -6
  - theory2 theory size 3
  - entry: theory0, 1 na 1
  - entry: theory0, 6 na 21
  - theory: theory3, linear, 6 na -1
  - entry: theory0, 7 na 25
  - theory: theory2, linear, 4 na -3
  - theory1 theory size 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

The candidates are:
  - theory0 theory size 10
  - theory: theory0, table, 0 and 0
  - entry: theory0, 2 and 5
  - entry: theory0, 11 and 41
  - theory3 theory size 3
  - theory: theory1, square, 2 and -6
  - theory2 theory size 3
  - entry: theory0, 1 and 1
  - entry: theory0, 6 and 21
  - theory: theory3, linear, 6 and -1
  - entry: theory0, 7 and 25
  - theory: theory2, linear, 4 and -3
  - theory1 theory size 2
The data are:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

{candidates: [(theory_size theory0 10) (theory theory0 table 0 0) (entry theory0 2 5) (entry theory0 11 41) (theory_size theory3 3) (theory theory1 square 2 -6) (theory_size theory2 3) (entry theory0 1 1) (entry theory0 6 21) (theory theory3 linear 6 -1) (entry theory0 7 25) (theory theory2 linear 4 -3) (theory_size theory1 2)], data: [(obs 1 1) (obs 2 5) (obs 11 41) (obs 6 21) (obs 7 25)], query: smallest_lossless_theory, rules: [(rule (a_theory_is_lossless_iff_it_predicts_every_observation_exactly)) (rule (choose_the_lossless_theory_of_least_size))], semantics: [(form linear "y = p1 * x + p2") (form square "y = x * x + p2") (form constant "y = p2") (form table "y = entry(x)")]}

Die Kandidaten sind:
  - theory0 Theorie Größe 10
  - Theorie: theory0, Tisch, 0 und 0
  - Eintrag: theory0, 2 und 5
  - Eintrag: theory0, 11 und 41
  - theory3 Theorie Größe 3
  - Theorie: theory1, square, 2 und -6
  - theory2 Theorie Größe 3
  - Eintrag: theory0, 1 und 1
  - Eintrag: theory0, 6 und 21
  - Theorie: theory3, linear, 6 und -1
  - Eintrag: theory0, 7 und 25
  - Theorie: theory2, linear, 4 und -3
  - theory1 Theorie Größe 2
Die Daten sind:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Die Regeln sind:
  - Regel ein Theorie werden verlustfrei gdw. er vorhersagen jeder Beobachtung genau
  - Regel wählen der verlustfrei Theorie aus geringst Größe
Die Semantik ist: linear formen y = p1 * x + p2; square formen y = x * x + p2; constant formen y = p2; der Tisch formen y = entry(x).
Was smallest verlustfrei Theorie?

Кандѝда̄т:
  - theory0 тѐо̄рија величѝна 10
  - тѐо̄рија: theory0, сто̑л, 0 и 0
  - одредница: theory0, 2 и 5
  - одредница: theory0, 11 и 41
  - theory3 тѐо̄рија величѝна 3
  - тѐо̄рија: theory1, square, 2 и -6
  - theory2 тѐо̄рија величѝна 3
  - одредница: theory0, 1 и 1
  - одредница: theory0, 6 и 21
  - тѐо̄рија: theory3, linear, 6 и -1
  - одредница: theory0, 7 и 25
  - тѐо̄рија: theory2, linear, 4 и -3
  - theory1 тѐо̄рија величѝна 2
Податци:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Пра̏вило:
  - пра̏вило тѐо̄рија би̏ти lossless iff оно predvidjeti сва̏кӣ опа́жа̄ње тачно
  - пра̏вило изабрати lossless тѐо̄рија od minimalan величѝна
Сема̀нтика: linear oblik y = p1 * x + p2; square oblik y = x * x + p2; constant oblik y = p2; сто̑л oblik y = entry(x).
Smallest lossless тѐо̄рија kakav?

Ehdokkaat:
  - theory0 teoria koko 10
  - teoria: theory0, pöytä, 0 ja 0
  - artikkeli: theory0, 2 ja 5
  - artikkeli: theory0, 11 ja 41
  - theory3 teoria koko 3
  - teoria: theory1, square, 2 ja -6
  - theory2 teoria koko 3
  - artikkeli: theory0, 1 ja 1
  - artikkeli: theory0, 6 ja 21
  - teoria: theory3, linear, 6 ja -1
  - artikkeli: theory0, 7 ja 25
  - teoria: theory2, linear, 4 ja -3
  - theory1 teoria koko 2
Tieto:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Säännöt:
  - sääntö teoria tulla häviötön joss se ennakoida jokainen havainnointi täsmälleen
  - sääntö valita häviötön teoria vaille vähin koko
Semantiikka: linear muotoilla y = p1 * x + p2; square muotoilla y = x * x + p2; constant muotoilla y = p2; pöytä muotoilla y = entry(x).
Mikä smallest häviötön teoria?

候选项如下：
  - theory0的理论规模是10
  - 的理论是：theory0、桌子、0和0
  - 的条目是：theory0、2和5
  - 的条目是：theory0、11和41
  - theory3的理论规模是3
  - 的理论是：theory1、square、2和-6
  - theory2的理论规模是3
  - 的条目是：theory0、1和1
  - 的条目是：theory0、6和21
  - 的理论是：theory3、linear、6和-1
  - 的条目是：theory0、7和25
  - 的理论是：theory2、linear、4和-3
  - theory1的理论规模是2
数据如下：
  - 1观察到1
  - 2观察到5
  - 11观察到41
  - 6观察到21
  - 7观察到25
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

候補者:
  - theory010理論大きさ
  - 理論:theory0, 台, 0と0
  - 項目:theory0, 2と5
  - 項目:theory0, 11と41
  - theory33理論大きさ
  - 理論:theory1, square, 2と-6
  - theory23理論大きさ
  - 項目:theory0, 1と1
  - 項目:theory0, 6と21
  - 理論:theory3, linear, 6と-1
  - 項目:theory0, 7と25
  - 理論:theory2, linear, 4と-3
  - theory12理論大きさ
資料:
  - 11obs
  - 25obs
  - 1141obs
  - 621obs
  - 725obs
規則:規則:理論れるロスレスiffこれ予言する凡ゆる観察正確に; 規則:選ぶロスレス理論の中の最小の大きさ.
意味論:lineary = p1 * x + p2形作る; squarey = x * x + p2形作る; constanty = p2形作る; 台y = entry(x)形作る.
smallestロスレス理論何と?

Adaylar:
  - theory0 10 kuram boyut
  - kuram: theory0, masa, 0 ve 0
  - entry: theory0, 2 ve 5
  - entry: theory0, 11 ve 41
  - theory3 3 kuram boyut
  - kuram: theory1, square, 2 ve -6
  - theory2 3 kuram boyut
  - entry: theory0, 1 ve 1
  - entry: theory0, 6 ve 21
  - kuram: theory3, linear, 6 ve -1
  - entry: theory0, 7 ve 25
  - kuram: theory2, linear, 4 ve -3
  - theory1 2 kuram boyut
Veriler:
  - 1 1 obs
  - 2 5 obs
  - 11 41 obs
  - 6 21 obs
  - 7 25 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

مُرَشَّح:
  - نَظَرِيَّة مَقَاس theory0 10
  - نَظَرِيَّة: theory0، طَاوِلَة، 0 وَـ 0
  - مَدْخَل: theory0، 2 وَـ 5
  - مَدْخَل: theory0، 11 وَـ 41
  - نَظَرِيَّة مَقَاس theory3 3
  - نَظَرِيَّة: theory1، square، 2 وَـ -6
  - نَظَرِيَّة مَقَاس theory2 3
  - مَدْخَل: theory0، 1 وَـ 1
  - مَدْخَل: theory0، 6 وَـ 21
  - نَظَرِيَّة: theory3، linear، 6 وَـ -1
  - مَدْخَل: theory0، 7 وَـ 25
  - نَظَرِيَّة: theory2، linear، 4 وَـ -3
  - نَظَرِيَّة مَقَاس theory1 2
بَيَانَات:
  - obs 1 1
  - obs 2 5
  - obs 11 41
  - obs 6 21
  - obs 7 25
قَانُون:
  - قَانُون نَظَرِيَّة كَانَ lossless iff هُوَ تَنَبَّأَ كُلّ رَصْد بِالضَّبْط
  - قَانُون اِخْتَارَ الـ lossless نَظَرِيَّة مِنْ أَقَلَّ مَقَاس
عِلْم اَلْمَعَانِي: شَكَّلَ linear y = p1 * x + p2؛ شَكَّلَ square y = x * x + p2؛ شَكَّلَ constant y = p2؛ شَكَّلَ الـ طَاوِلَة y = entry(x).
smallest lossless نَظَرِيَّة مَاذَا؟

Კანდიდატები:
  - theory0 10 თეორია ზომა
  - თეორია: theory0, მაგიდა, 0 და 0
  - სასათაურო სიტყვა: theory0, 2 და 5
  - სასათაურო სიტყვა: theory0, 11 და 41
  - theory3 3 თეორია ზომა
  - თეორია: theory1, square, 2 და -6
  - theory2 3 თეორია ზომა
  - სასათაურო სიტყვა: theory0, 1 და 1
  - სასათაურო სიტყვა: theory0, 6 და 21
  - თეორია: theory3, linear, 6 და -1
  - სასათაურო სიტყვა: theory0, 7 და 25
  - თეორია: theory2, linear, 4 და -3
  - theory1 2 თეორია ზომა
Მონაცემები:
  - 1 1 obs
  - 2 5 obs
  - 11 41 obs
  - 6 21 obs
  - 7 25 obs
Წესი:
  - წესი თეორია ყოფნა უდანაკარგო iff ის predict ყველა დაკვირვება ზუსტად
  - წესი ამორჩევა უდანაკარგო თეორია of least ზომა
Სემანტიკა: linear y = p1 * x + p2 ბლანკი; square y = x * x + p2 ბლანკი; constant y = p2 ბლანკი; მაგიდა y = entry(x) ბლანკი.
Smallest უდანაკარგო თეორია რა?

Kaiwhakauru:
  - ariā size theory0 10
  - ariā: theory0, tēpu, 0 me 0
  - tāurunga: theory0, 2 me 5
  - tāurunga: theory0, 11 me 41
  - ariā size theory3 3
  - ariā: theory1, square, 2 me -6
  - ariā size theory2 3
  - tāurunga: theory0, 1 me 1
  - tāurunga: theory0, 6 me 21
  - ariā: theory3, linear, 6 me -1
  - tāurunga: theory0, 7 me 25
  - ariā: theory2, linear, 4 me -3
  - ariā size theory1 2
Hōtuku:
  - obs 1 1
  - obs 2 5
  - obs 11 41
  - obs 6 21
  - obs 7 25
Rekureihana:
  - rekureihana ariā is lossless iff it matakite every observation pū
  - rekureihana whiri te lossless ariā o least size
Semantics: āhua linear y = p1 * x + p2; āhua square y = x * x + p2; āhua constant y = p2; āhua te tēpu y = entry(x).
Smallest lossless ariā unutai?

Candidates:
  - theory0 lý thuyết kích thước 10
  - lý thuyết: theory0, bàn, 0 và 0
  - mục từ: theory0, 2 và 5
  - mục từ: theory0, 11 và 41
  - theory3 lý thuyết kích thước 3
  - lý thuyết: theory1, square, 2 và -6
  - theory2 lý thuyết kích thước 3
  - mục từ: theory0, 1 và 1
  - mục từ: theory0, 6 và 21
  - lý thuyết: theory3, linear, 6 và -1
  - mục từ: theory0, 7 và 25
  - lý thuyết: theory2, linear, 4 và -3
  - theory1 lý thuyết kích thước 2
Dữ liệu:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Quy tắc:
  - quy tắc lý thuyết được lossless iff nó dự báo mỗi observation đúng rồi
  - quy tắc chọn the lossless lý thuyết bằng least kích thước
Ngữ nghĩa: linear làm thành y = p1 * x + p2; square làm thành y = x * x + p2; constant làm thành y = p2; bàn làm thành y = entry(x).
Smallest lossless lý thuyết gì?

ผู้สมัคร:
  - theory0ทฤษฎีขนาด10
  - ทฤษฎี:theory0, โต๊ะ, 0และ0
  - entry:theory0, 2และ5
  - entry:theory0, 11และ41
  - theory3ทฤษฎีขนาด3
  - ทฤษฎี:theory1, square, 2และ-6
  - theory2ทฤษฎีขนาด3
  - entry:theory0, 1และ1
  - entry:theory0, 6และ21
  - ทฤษฎี:theory3, linear, 6และ-1
  - entry:theory0, 7และ25
  - ทฤษฎี:theory2, linear, 4และ-3
  - theory1ทฤษฎีขนาด2
ข้อมูล:
  - 1obs1
  - 2obs5
  - 11obs41
  - 6obs21
  - 7obs25
กฎ:กฎ:ทฤษฎีถูกlosslessiffมันทำนายทุกการสังเกตexactly; กฎ:เลือกlosslessทฤษฎีของleastขนาด.
อรรถศาสตร์:linearรูปร่างy = p1 * x + p2; squareรูปร่างy = x * x + p2; constantรูปร่างy = p2; โต๊ะรูปร่างy = entry(x).
smallestlosslessทฤษฎีอะไร?

வேட்பாளர்:
  - theory0 10 theory size
  - theory: theory0, மேசை, 0 மற்றும் 0
  - உள்நுழைவதற்கு அனுமதி: theory0, 2 மற்றும் 5
  - உள்நுழைவதற்கு அனுமதி: theory0, 11 மற்றும் 41
  - theory3 3 theory size
  - theory: theory1, square, 2 மற்றும் -6
  - theory2 3 theory size
  - உள்நுழைவதற்கு அனுமதி: theory0, 1 மற்றும் 1
  - உள்நுழைவதற்கு அனுமதி: theory0, 6 மற்றும் 21
  - theory: theory3, linear, 6 மற்றும் -1
  - உள்நுழைவதற்கு அனுமதி: theory0, 7 மற்றும் 25
  - theory: theory2, linear, 4 மற்றும் -3
  - theory1 2 theory size
தரவுகள்:
  - 1 1 obs
  - 2 5 obs
  - 11 41 obs
  - 6 21 obs
  - 7 25 obs
rules: rule theory படு lossless iff it கணி ஒவ்வொரு observation exactly; rule choose lossless theory கொண்ட least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; மேசை y = entry(x) form.
smallest lossless theory என்ன?

Wagombea ni:
  - theory0 theory size 10
  - theory: theory0, meza, 0 na 0
  - entry: theory0, 2 na 5
  - entry: theory0, 11 na 41
  - theory3 theory size 3
  - theory: theory1, square, 2 na -6
  - theory2 theory size 3
  - entry: theory0, 1 na 1
  - entry: theory0, 6 na 21
  - theory: theory3, linear, 6 na -1
  - entry: theory0, 7 na 25
  - theory: theory2, linear, 4 na -3
  - theory1 theory size 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

Candidates:
  - theory0 10 theory size
  - theory: theory0, bikááʼ adání, 0 dóó 0
  - entry: theory0, 2 dóó 5
  - entry: theory0, 11 dóó 41
  - theory3 3 theory size
  - theory: theory1, square, 2 dóó -6
  - theory2 3 theory size
  - entry: theory0, 1 dóó 1
  - entry: theory0, 6 dóó 21
  - theory: theory3, linear, 6 dóó -1
  - entry: theory0, 7 dóó 25
  - theory: theory2, linear, 4 dóó -3
  - theory1 2 theory size
Data:
  - 1 1 obs
  - 2 5 obs
  - 11 41 obs
  - 6 21 obs
  - 7 25 obs
Bee hazʼáanii:
  - bee hazʼáanii theory átʼé lossless iff it predict every observation exactly
  - bee hazʼáanii choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; bikááʼ adání y = entry(x) form.
Smallest lossless theory haʼátʼíísh?

Candidates:
  - theory0 10 theory size
  - theory: theory0, table, 0 aamma 0
  - entry: theory0, 2 aamma 5
  - entry: theory0, 11 aamma 41
  - theory3 3 theory size
  - theory: theory1, square, 2 aamma -6
  - theory2 3 theory size
  - entry: theory0, 1 aamma 1
  - entry: theory0, 6 aamma 21
  - theory: theory3, linear, 6 aamma -1
  - entry: theory0, 7 aamma 25
  - theory: theory2, linear, 4 aamma -3
  - theory1 2 theory size
Data:
  - 1 1 obs
  - 2 5 obs
  - 11 41 obs
  - 6 21 obs
  - 7 25 obs
Rules: rule theory a lossless iff una predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 blanketti; square y = x * x + p2 blanketti; constant y = p2 blanketti; table y = entry(x) blanketti.
Smallest lossless theory what?

Candidates:
  - theory0 theory size 10
  - theory: theory0, table, 0 na 0
  - entry: theory0, 2 na 5
  - entry: theory0, 11 na 41
  - theory3 theory size 3
  - theory: theory1, square, 2 na -6
  - theory2 theory size 3
  - entry: theory0, 1 na 1
  - entry: theory0, 6 na 21
  - theory: theory3, linear, 6 na -1
  - entry: theory0, 7 na 25
  - theory: theory2, linear, 4 na -3
  - theory1 theory size 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory bilong least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory0 theory size 10
  - theory: theory0, table, 0 0
  - entry: theory0, 2 5
  - entry: theory0, 11 41
  - theory3 theory size 3
  - theory: theory1, square, 2 -6
  - theory2 theory size 3
  - entry: theory0, 1 1
  - entry: theory0, 6 21
  - theory: theory3, linear, 6 -1
  - entry: theory0, 7 25
  - theory: theory2, linear, 4 -3
  - theory1 theory size 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Nikanixi:
  - nikanixi theory is lossless iff it predict every observation exactly
  - nikanixi choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory kwèch?

Candidates:
  - theory0 theory size 10
  - theory: theory0, table, 0 а 0
  - entry: theory0, 2 а 5
  - entry: theory0, 11 а 41
  - theory3 theory size 3
  - theory: theory1, square, 2 а -6
  - theory2 theory size 3
  - entry: theory0, 1 а 1
  - entry: theory0, 6 а 21
  - theory: theory3, linear, 6 а -1
  - entry: theory0, 7 а 25
  - theory: theory2, linear, 4 а -3
  - theory1 theory size 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Rules:
  - rule theory хила lossless iff it predict дерриг observation exactly
  - rule хержа lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory фу?

후보자:
  - theory0 10 이론 크기
  - 이론: theory0, 테이블, 0 0
  - 항목: theory0, 2 5
  - 항목: theory0, 11 41
  - theory3 3 이론 크기
  - 이론: theory1, square, 2 -6
  - theory2 3 이론 크기
  - 항목: theory0, 1 1
  - 항목: theory0, 6 21
  - 이론: theory3, linear, 6 -1
  - 항목: theory0, 7 25
  - 이론: theory2, linear, 4 -3
  - theory1 2 이론 크기
자료:
  - 1 1 obs
  - 2 5 obs
  - 11 41 obs
  - 6 21 obs
  - 7 25 obs
규칙: 규칙 이론 is lossless iff 이것 예언하다 각 관찰 정확하게; 규칙 고르다 lossless 이론...의 가장 적게 크기.
의미론: linear y = p1 * x + p2 형상; square y = x * x + p2 형상; constant y = p2 형상; 테이블 y = entry(x) 형상.
smallest lossless 이론 무엇?

Kandidatu:
  - theory0 10 theory tamaina
  - theory: theory0, mahai, 0 eta 0
  - sarrera: theory0, 2 eta 5
  - sarrera: theory0, 11 eta 41
  - theory3 3 theory tamaina
  - theory: theory1, square, 2 eta -6
  - theory2 3 theory tamaina
  - sarrera: theory0, 1 eta 1
  - sarrera: theory0, 6 eta 21
  - theory: theory3, linear, 6 eta -1
  - sarrera: theory0, 7 eta 25
  - theory: theory2, linear, 4 eta -3
  - theory1 2 theory tamaina
Data:
  - 1 1 obs
  - 2 5 obs
  - 11 41 obs
  - 6 21 obs
  - 7 25 obs
Arau:
  - arau bat theory izan lossless iff it aurresan every observation exactly
  - arau aukeratu the lossless theory of least tamaina
Semantics: linear y = p1 * x + p2 forma; square y = x * x + p2 forma; constant y = p2 forma; mahai y = entry(x) forma.
Smallest lossless theory zer?

ᎠᏙᎩᏯᏍᎩ:
  - theory0 theory size 10
  - theory: theory0, ᎦᏍᎩᎶ, 0 ᎠᎴ 0
  - entry: theory0, 2 ᎠᎴ 5
  - entry: theory0, 11 ᎠᎴ 41
  - theory3 theory size 3
  - theory: theory1, square, 2 ᎠᎴ -6
  - theory2 theory size 3
  - entry: theory0, 1 ᎠᎴ 1
  - entry: theory0, 6 ᎠᎴ 21
  - theory: theory3, linear, 6 ᎠᎴ -1
  - entry: theory0, 7 ᎠᎴ 25
  - theory: theory2, linear, 4 ᎠᎴ -3
  - theory1 theory size 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ᎦᏍᎩᎶ form y = entry(x).
What smallest lossless theory?

Candidates:
  - theory0 theory chhika 10
  - theory: theory0, patacha, 0 0
  - entry: theory0, 2 5
  - entry: theory0, 11 41
  - theory3 theory chhika 3
  - theory: theory1, square, 2 -6
  - theory2 theory chhika 3
  - entry: theory0, 1 1
  - entry: theory0, 6 21
  - theory: theory3, linear, 6 -1
  - entry: theory0, 7 25
  - theory: theory2, linear, 4 -3
  - theory1 theory chhika 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Rules:
  - rule theory tiyay lossless iff it predict tukuy observation exactly
  - rule akllay lossless theory of least chhika
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; patacha form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory0 10 тиориэ size
  - тиориэ: theory0, table, 0 ыкӏи 0
  - entry: theory0, 2 ыкӏи 5
  - entry: theory0, 11 ыкӏи 41
  - theory3 3 тиориэ size
  - тиориэ: theory1, square, 2 ыкӏи -6
  - theory2 3 тиориэ size
  - entry: theory0, 1 ыкӏи 1
  - entry: theory0, 6 ыкӏи 21
  - тиориэ: theory3, linear, 6 ыкӏи -1
  - entry: theory0, 7 ыкӏи 25
  - тиориэ: theory2, linear, 4 ыкӏи -3
  - theory1 2 тиориэ size
Data:
  - 1 1 obs
  - 2 5 obs
  - 11 41 obs
  - 6 21 obs
  - 7 25 obs
Rules: rule тиориэ is lossless iff it predict every observation exactly; rule choose the lossless тиориэ of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless тиориэ сыд?

Candidates:
  - theory0 theory size 10
  - theory: theory0, rooj, 0 thiab 0
  - entry: theory0, 2 thiab 5
  - entry: theory0, 11 thiab 41
  - theory3 theory size 3
  - theory: theory1, square, 2 thiab -6
  - theory2 theory size 3
  - entry: theory0, 1 thiab 1
  - entry: theory0, 6 thiab 21
  - theory: theory3, linear, 6 thiab -1
  - entry: theory0, 7 thiab 25
  - theory: theory2, linear, 4 thiab -3
  - theory1 theory size 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Cai: cai theory is lossless iff nws predict every observation exactly; cai choose lossless theory of least size.
Lub ntsiab: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; rooj form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory0 theory size 10
  - theory: theory0, table, 0 0
  - entry: theory0, 2 5
  - entry: theory0, 11 41
  - theory3 theory size 3
  - theory: theory1, square, 2 -6
  - theory2 theory size 3
  - entry: theory0, 1 1
  - entry: theory0, 6 21
  - theory: theory3, linear, 6 -1
  - entry: theory0, 7 25
  - theory: theory2, linear, 4 -3
  - theory1 theory size 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of wy krook size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory ining-jak?

Candidates:
  - theory0 theory size 10
  - theory: theory0, table, 0 micha' 0
  - entry: theory0, 2 micha' 5
  - entry: theory0, 11 micha' 41
  - theory3 theory size 3
  - theory: theory1, square, 2 micha' -6
  - theory2 theory size 3
  - entry: theory0, 1 micha' 1
  - entry: theory0, 6 micha' 21
  - theory: theory3, linear, 6 micha' -1
  - entry: theory0, 7 micha' 25
  - theory: theory2, linear, 4 micha' -3
  - theory1 theory size 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory nanta?

Candidates:
  - theory0 10 theory size
  - theory: theory0, table, 0 カ 0
  - entry: theory0, 2 カ 5
  - entry: theory0, 11 カ 41
  - theory3 3 theory size
  - theory: theory1, square, 2 カ -6
  - theory2 3 theory size
  - entry: theory0, 1 カ 1
  - entry: theory0, 6 カ 21
  - theory: theory3, linear, 6 カ -1
  - entry: theory0, 7 カ 25
  - theory: theory2, linear, 4 カ -3
  - theory1 2 theory size
Data:
  - 1 1 obs
  - 2 5 obs
  - 11 41 obs
  - 6 21 obs
  - 7 25 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 ノカ; square y = x * x + p2 ノカ; constant y = p2 ノカ; table y = entry(x) ノカ.
Smallest lossless theory what?

Candidates:
  - theory0 theory size 10
  - theory: theory0, table, 0 ынкъам 0
  - entry: theory0, 2 ынкъам 5
  - entry: theory0, 11 ынкъам 41
  - theory3 theory size 3
  - theory: theory1, square, 2 ынкъам -6
  - theory2 theory size 3
  - entry: theory0, 1 ынкъам 1
  - entry: theory0, 6 ынкъам 21
  - theory: theory3, linear, 6 ынкъам -1
  - entry: theory0, 7 ынкъам 25
  - theory: theory2, linear, 4 ынкъам -3
  - theory1 theory size 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory0 theory size 10
  - theory: theory0, table, 0 yéetel 0
  - entry: theory0, 2 yéetel 5
  - entry: theory0, 11 yéetel 41
  - theory3 theory size 3
  - theory: theory1, square, 2 yéetel -6
  - theory2 theory size 3
  - entry: theory0, 1 yéetel 1
  - entry: theory0, 6 yéetel 21
  - theory: theory3, linear, 6 yéetel -1
  - entry: theory0, 7 yéetel 25
  - theory: theory2, linear, 4 yéetel -3
  - theory1 theory size 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Rules:
  - rule theory yan lossless iff it predict every observation exactly
  - rule yéey lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory0 theory size 10
  - theory: theory0, mę́soną, 0 0
  - entry: theory0, 2 5
  - entry: theory0, 11 41
  - theory3 theory size 3
  - theory: theory1, square, 2 -6
  - theory2 theory size 3
  - entry: theory0, 1 1
  - entry: theory0, 6 21
  - theory: theory3, linear, 6 -1
  - entry: theory0, 7 25
  - theory: theory2, linear, 4 -3
  - theory1 theory size 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Rules:
  - rule theory is lossless iff ą́wąną predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mę́soną form y = entry(x).
Smallest lossless theory híli?

Candidates:
  - theory0 10 theory size
  - theory: theory0, table, 0 na 0
  - entry: theory0, 2 na 5
  - entry: theory0, 11 na 41
  - theory3 3 theory size
  - theory: theory1, square, 2 na -6
  - theory2 3 theory size
  - entry: theory0, 1 na 1
  - entry: theory0, 6 na 21
  - theory: theory3, linear, 6 na -1
  - entry: theory0, 7 na 25
  - theory: theory2, linear, 4 na -3
  - theory1 2 theory size
Data:
  - 1 1 obs
  - 2 5 obs
  - 11 41 obs
  - 6 21 obs
  - 7 25 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory0 theory size 10
  - theory: theory0, table, 0 0
  - entry: theory0, 2 5
  - entry: theory0, 11 41
  - theory3 theory size 3
  - theory: theory1, square, 2 -6
  - theory2 theory size 3
  - entry: theory0, 1 1
  - entry: theory0, 6 21
  - theory: theory3, linear, 6 -1
  - entry: theory0, 7 25
  - theory: theory2, linear, 4 -3
  - theory1 theory size 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory0 10 theory size
  - theory: theory0, table, 0 0
  - entry: theory0, 2 5
  - entry: theory0, 11 41
  - theory3 3 theory size
  - theory: theory1, square, 2 -6
  - theory2 3 theory size
  - entry: theory0, 1 1
  - entry: theory0, 6 21
  - theory: theory3, linear, 6 -1
  - entry: theory0, 7 25
  - theory: theory2, linear, 4 -3
  - theory1 2 theory size
Data:
  - 1 1 obs
  - 2 5 obs
  - 11 41 obs
  - 6 21 obs
  - 7 25 obs
Rules:
  - rule maya theory is lossless iff it predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory0 theory ʻǁnàhã 10
  - theory: theory0, table, 0 ǂʻá 0
  - entry: theory0, 2 ǂʻá 5
  - entry: theory0, 11 ǂʻá 41
  - theory3 theory ʻǁnàhã 3
  - theory: theory1, square, 2 ǂʻá -6
  - theory2 theory ʻǁnàhã 3
  - entry: theory0, 1 ǂʻá 1
  - entry: theory0, 6 ǂʻá 21
  - theory: theory3, linear, 6 ǂʻá -1
  - entry: theory0, 7 ǂʻá 25
  - theory: theory2, linear, 4 ǂʻá -3
  - theory1 theory ʻǁnàhã 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Rules:
  - rule theory ǀîi lossless iff èh predict every observation exactly
  - rule choose lossless theory of least ʻǁnàhã
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory0 10 theory size
  - theory: theory0, остол, 0 0
  - entry: theory0, 2 5
  - entry: theory0, 11 41
  - theory3 3 theory size
  - theory: theory1, square, 2 -6
  - theory2 3 theory size
  - entry: theory0, 1 1
  - entry: theory0, 6 21
  - theory: theory3, linear, 6 -1
  - entry: theory0, 7 25
  - theory: theory2, linear, 4 -3
  - theory1 2 theory size
Data:
  - 1 1 obs
  - 2 5 obs
  - 11 41 obs
  - 6 21 obs
  - 7 25 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; остол y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory0 theory size 10
  - theory: theory0, table, 0 0
  - entry: theory0, 2 5
  - entry: theory0, 11 41
  - theory3 theory size 3
  - theory: theory1, square, 2 -6
  - theory2 theory size 3
  - entry: theory0, 1 1
  - entry: theory0, 6 21
  - theory: theory3, linear, 6 -1
  - entry: theory0, 7 25
  - theory: theory2, linear, 4 -3
  - theory1 theory size 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory0 10 theory size
  - theory: theory0, table, 0 0
  - entry: theory0, 2 5
  - entry: theory0, 11 41
  - theory3 3 theory size
  - theory: theory1, square, 2 -6
  - theory2 3 theory size
  - entry: theory0, 1 1
  - entry: theory0, 6 21
  - theory: theory3, linear, 6 -1
  - entry: theory0, 7 25
  - theory: theory2, linear, 4 -3
  - theory1 2 theory size
Data:
  - 1 1 obs
  - 2 5 obs
  - 11 41 obs
  - 6 21 obs
  - 7 25 obs
Rules:
  - rule theory is lossless iff kitu predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory0 theory size 10
  - theory: theory0, mesa, 0 0
  - entry: theory0, 2 5
  - entry: theory0, 11 41
  - theory3 theory size 3
  - theory: theory1, square, 2 -6
  - theory2 theory size 3
  - entry: theory0, 1 1
  - entry: theory0, 6 21
  - theory: theory3, linear, 6 -1
  - entry: theory0, 7 25
  - theory: theory2, linear, 4 -3
  - theory1 theory size 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mesa form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory0 theory size 10
  - theory: theory0, table, 0 0
  - entry: theory0, 2 5
  - entry: theory0, 11 41
  - theory3 theory size 3
  - theory: theory1, square, 2 -6
  - theory2 theory size 3
  - entry: theory0, 1 1
  - entry: theory0, 6 21
  - theory: theory3, linear, 6 -1
  - entry: theory0, 7 25
  - theory: theory2, linear, 4 -3
  - theory1 theory size 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Rules:
  - rule theory nemi lossless iff yaja predict every observation exactly
  - rule choose ne lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ne table form y = entry(x).
Smallest lossless theory tay?

Les candidats sont:
  - theory0 théorie taille 10
  - théorie: theory0, table, 0 et 0
  - article: theory0, 2 et 5
  - article: theory0, 11 et 41
  - theory3 théorie taille 3
  - théorie: theory1, square, 2 et -6
  - theory2 théorie taille 3
  - article: theory0, 1 et 1
  - article: theory0, 6 et 21
  - théorie: theory3, linear, 6 et -1
  - article: theory0, 7 et 25
  - théorie: theory2, linear, 4 et -3
  - theory1 théorie taille 2
Les données sont:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Les règles sont:
  - règle un théorie être lossless ssi il prédire tout observation exactement
  - règle choisir le lossless théorie du moindre taille
La sémantique est : linear former y = p1 * x + p2 ; square former y = x * x + p2 ; constant former y = p2 ; la table former y = entry(x).
Quoi smallest lossless théorie ?

Kandidato:
  - theory0 teorio grandeco 10
  - teorio: theory0, tablo, 0 kaj 0
  - entry: theory0, 2 kaj 5
  - entry: theory0, 11 kaj 41
  - theory3 teorio grandeco 3
  - teorio: theory1, square, 2 kaj -6
  - theory2 teorio grandeco 3
  - entry: theory0, 1 kaj 1
  - entry: theory0, 6 kaj 21
  - teorio: theory3, linear, 6 kaj -1
  - entry: theory0, 7 kaj 25
  - teorio: theory2, linear, 4 kaj -3
  - theory1 teorio grandeco 2
Datumo:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Regulo: regulo teorio egali lossless iff ĝi predict ĉiu observo ekzakte; regulo elekti lossless teorio de plej malmulta grandeco.
Semantics: linear formi y = p1 * x + p2; square formi y = x * x + p2; constant formi y = p2; tablo formi y = entry(x).
Smallest lossless teorio kio?

Indulók:
  - theory0 elmélet méret 10
  - elmélet: theory0, asztal, 0 és 0
  - szócikk: theory0, 2 és 5
  - szócikk: theory0, 11 és 41
  - theory3 elmélet méret 3
  - elmélet: theory1, square, 2 és -6
  - theory2 elmélet méret 3
  - szócikk: theory0, 1 és 1
  - szócikk: theory0, 6 és 21
  - elmélet: theory3, linear, 6 és -1
  - szócikk: theory0, 7 és 25
  - elmélet: theory2, linear, 4 és -3
  - theory1 elmélet méret 2
Adat:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Szabályok:
  - szabály elmélet van veszteségmentes acsa az megjósol minden megfigyelés pontosan
  - szabály kiválaszt a veszteségmentes elmélet of legkisebb méret
Szemantika: linear kialakít y = p1 * x + p2; square kialakít y = x * x + p2; constant kialakít y = p2; a asztal kialakít y = entry(x).
Smallest veszteségmentes elmélet melyik?

候選人:
  - theory0theory size10
  - theory:theory0, 檯, 0及0
  - entry:theory0, 2及5
  - entry:theory0, 11及41
  - theory3theory size3
  - theory:theory1, square, 2及-6
  - theory2theory size3
  - entry:theory0, 1及1
  - entry:theory0, 6及21
  - theory:theory3, linear, 6及-1
  - entry:theory0, 7及25
  - theory:theory2, linear, 4及-3
  - theory1theory size2
數據:
  - 1obs1
  - 2obs5
  - 11obs41
  - 6obs21
  - 7obs25
rules:rule:一theory是losslessiffitpredict每observationexactly; rule:揀losslesstheory...嘅leastsize.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; 檯formy = entry(x).
smallest lossless theory乜嘢?

Candidates:
  - theory0 theory size 10
  - theory: theory0, table, 0 とぅ 0
  - entry: theory0, 2 とぅ 5
  - entry: theory0, 11 とぅ 41
  - theory3 theory size 3
  - theory: theory1, square, 2 とぅ -6
  - theory2 theory size 3
  - entry: theory0, 1 とぅ 1
  - entry: theory0, 6 とぅ 21
  - theory: theory3, linear, 6 とぅ -1
  - entry: theory0, 7 とぅ 25
  - theory: theory2, linear, 4 とぅ -3
  - theory1 theory size 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Rules: rule theory 有ん lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Үміткер:
  - theory0 теория мөлшер 10
  - теория: theory0, үстел, 0 және 0
  - entry: theory0, 2 және 5
  - entry: theory0, 11 және 41
  - theory3 теория мөлшер 3
  - теория: theory1, square, 2 және -6
  - theory2 теория мөлшер 3
  - entry: theory0, 1 және 1
  - entry: theory0, 6 және 21
  - теория: theory3, linear, 6 және -1
  - entry: theory0, 7 және 25
  - теория: theory2, linear, 4 және -3
  - theory1 теория мөлшер 2
Деректер:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Ереже: ереже теория is lossless iff ол predict әр бақылау exactly; ереже таңдау lossless теория туралы least мөлшер.
Семантикалық: linear пішін y = p1 * x + p2; square пішін y = x * x + p2; constant пішін y = p2; үстел пішін y = entry(x).
Smallest lossless теория не?

מועמדת:
  - theory0 תּוֹרָה גֹּדֶל 10
  - תּוֹרָה: theory0, טַבְלָה, 0 וְ־ 0
  - entry: theory0, 2 וְ־ 5
  - entry: theory0, 11 וְ־ 41
  - theory3 תּוֹרָה גֹּדֶל 3
  - תּוֹרָה: theory1, square, 2 וְ־ -6
  - theory2 תּוֹרָה גֹּדֶל 3
  - entry: theory0, 1 וְ־ 1
  - entry: theory0, 6 וְ־ 21
  - תּוֹרָה: theory3, linear, 6 וְ־ -1
  - entry: theory0, 7 וְ־ 25
  - תּוֹרָה: theory2, linear, 4 וְ־ -3
  - theory1 תּוֹרָה גֹּדֶל 2
נְתוּנִים:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
מָשַׁל:
  - מָשַׁל אַחַת תּוֹרָה הוא lossless אםם זֶה predict כֹּל תַּצְפִּית בדיוק
  - מָשַׁל בחר ה־ lossless תּוֹרָה שֶׁל least גֹּדֶל
תורת המשמעים: linear צורה y = p1 * x + p2; square צורה y = x * x + p2; constant צורה y = p2; טַבְלָה ה־ צורה y = entry(x).
איזה smallest lossless תּוֹרָה?

Candidates:
  - theory0 theory size 10
  - theory: theory0, table, 0 დო 0
  - entry: theory0, 2 დო 5
  - entry: theory0, 11 დო 41
  - theory3 theory size 3
  - theory: theory1, square, 2 დო -6
  - theory2 theory size 3
  - entry: theory0, 1 დო 1
  - entry: theory0, 6 დო 21
  - theory: theory3, linear, 6 დო -1
  - entry: theory0, 7 დო 25
  - theory: theory2, linear, 4 დო -3
  - theory1 theory size 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Kandidat:
  - theory0 teori ukuran 10
  - teori: theory0, meja, 0 dan 0
  - lema: theory0, 2 dan 5
  - lema: theory0, 11 dan 41
  - theory3 teori ukuran 3
  - teori: theory1, square, 2 dan -6
  - theory2 teori ukuran 3
  - lema: theory0, 1 dan 1
  - lema: theory0, 6 dan 21
  - teori: theory3, linear, 6 dan -1
  - lema: theory0, 7 dan 25
  - teori: theory2, linear, 4 dan -3
  - theory1 teori ukuran 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Rules:
  - rule teori berada lossless iff it predict setiap observation tepat
  - rule memilih si lossless teori dari least ukuran
Semantik: linear formulir y = p1 * x + p2; square formulir y = x * x + p2; constant formulir y = p2; meja si formulir y = entry(x).
Smallest lossless teori apa?

បេក្ខជន:
  - theory0ទ្រឹស្ដីទំហំ10
  - ទ្រឹស្ដី:theory0, តុ, 0នឹង0
  - មេពាក្យ:theory0, 2នឹង5
  - មេពាក្យ:theory0, 11នឹង41
  - theory3ទ្រឹស្ដីទំហំ3
  - ទ្រឹស្ដី:theory1, square, 2នឹង-6
  - theory2ទ្រឹស្ដីទំហំ3
  - មេពាក្យ:theory0, 1នឹង1
  - មេពាក្យ:theory0, 6នឹង21
  - ទ្រឹស្ដី:theory3, linear, 6នឹង-1
  - មេពាក្យ:theory0, 7នឹង25
  - ទ្រឹស្ដី:theory2, linear, 4នឹង-3
  - theory1ទ្រឹស្ដីទំហំ2
ទិន្នន័យ:
  - 1obs1
  - 2obs5
  - 11obs41
  - 6obs21
  - 7obs25
ក្បួន:ក្បួន:ទ្រឹស្ដីត្រូវបានlosslessiffវាចាប់យាមរាល់គំនន់exactly; ក្បួន:រើសthelosslessទ្រឹស្ដីនៃleastទំហំ.
និឃណ្ដសាស្ត្រ:linearគ្រោងy = p1 * x + p2; squareគ្រោងy = x * x + p2; constantគ្រោងy = p2; តុគ្រោងy = entry(x).
smallestlosslessទ្រឹស្ដីអី?

ຜູ້ສະໝັກ:
  - theory0ທິດສະດີຂະຫນາດ10
  - ທິດສະດີ:theory0, ໂຕະ, 0ແລະ0
  - entry:theory0, 2ແລະ5
  - entry:theory0, 11ແລະ41
  - theory3ທິດສະດີຂະຫນາດ3
  - ທິດສະດີ:theory1, square, 2ແລະ-6
  - theory2ທິດສະດີຂະຫນາດ3
  - entry:theory0, 1ແລະ1
  - entry:theory0, 6ແລະ21
  - ທິດສະດີ:theory3, linear, 6ແລະ-1
  - entry:theory0, 7ແລະ25
  - ທິດສະດີ:theory2, linear, 4ແລະ-3
  - theory1ທິດສະດີຂະຫນາດ2
ຂໍ້ມູນ:
  - 1obs1
  - 2obs5
  - 11obs41
  - 6obs21
  - 7obs25
ກະຕິກາ:ກະຕິກາ:ທິດສະດີຢູ່losslessiffມັນທຳນວາຍທຸກobservationexactly; ກະຕິກາ:ເລືອກlosslessທິດສະດີຂອງleastຂະຫນາດ.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; ໂຕະformy = entry(x).
smallestlosslessທິດສະດີຫຍັງ?

candidates:
  - theory0 10 theory size
  - theory: theory0, బల్ల, 0 మరియు 0
  - entry: theory0, 2 మరియు 5
  - entry: theory0, 11 మరియు 41
  - theory3 3 theory size
  - theory: theory1, square, 2 మరియు -6
  - theory2 3 theory size
  - entry: theory0, 1 మరియు 1
  - entry: theory0, 6 మరియు 21
  - theory: theory3, linear, 6 మరియు -1
  - entry: theory0, 7 మరియు 25
  - theory: theory2, linear, 4 మరియు -3
  - theory1 2 theory size
data:
  - 1 1 obs
  - 2 5 obs
  - 11 41 obs
  - 6 21 obs
  - 7 25 obs
నియమం: నియమం theory ఉండు lossless iff it predict ప్రతి పరిశీలన exactly; నియమం choose lossless theory of least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; బల్ల y = entry(x) form.
smallest lossless theory ఏమిటి?

Candidates:
  - theory0 theory size 10
  - theory: theory0, table, 0 0
  - entry: theory0, 2 5
  - entry: theory0, 11 41
  - theory3 theory size 3
  - theory: theory1, square, 2 -6
  - theory2 theory size 3
  - entry: theory0, 1 1
  - entry: theory0, 6 21
  - theory: theory3, linear, 6 -1
  - entry: theory0, 7 25
  - theory: theory2, linear, 4 -3
  - theory1 theory size 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Rules: rule theory wà lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
What smallest lossless theory?

Candidates:
  - theory0 10 theory size
  - theory: theory0, table, 0 0
  - entry: theory0, 2 5
  - entry: theory0, 11 41
  - theory3 3 theory size
  - theory: theory1, square, 2 -6
  - theory2 3 theory size
  - entry: theory0, 1 1
  - entry: theory0, 6 21
  - theory: theory3, linear, 6 -1
  - entry: theory0, 7 25
  - theory: theory2, linear, 4 -3
  - theory1 2 theory size
Data:
  - 1 1 obs
  - 2 5 obs
  - 11 41 obs
  - 6 21 obs
  - 7 25 obs
Rules:
  - rule theory naiágúóli lossless iff it predict every observation exactly
  - rule choose the lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

candidates:
  - theory0 theory size 10
  - theory: theory0, table, 0 0
  - entry: theory0, 2 5
  - entry: theory0, 11 41
  - theory3 theory size 3
  - theory: theory1, square, 2 -6
  - theory2 theory size 3
  - entry: theory0, 1 1
  - entry: theory0, 6 21
  - theory: theory3, linear, 6 -1
  - entry: theory0, 7 25
  - theory: theory2, linear, 4 -3
  - theory1 theory size 2
data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
smallest lossless theory what?

Candidates:
  - theory0 theory size 10
  - theory: theory0, tafra, 0 0
  - entry: theory0, 2 5
  - entry: theory0, 11 41
  - theory3 theory size 3
  - theory: theory1, square, 2 -6
  - theory2 theory size 3
  - entry: theory0, 1 1
  - entry: theory0, 6 21
  - theory: theory3, linear, 6 -1
  - entry: theory0, 7 25
  - theory: theory2, linear, 4 -3
  - theory1 theory size 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; tafra form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory0 theory size 10
  - theory: theory0, táxemésėhestȯtse, 0 0
  - entry: theory0, 2 5
  - entry: theory0, 11 41
  - theory3 theory size 3
  - theory: theory1, square, 2 -6
  - theory2 theory size 3
  - entry: theory0, 1 1
  - entry: theory0, 6 21
  - theory: theory3, linear, 6 -1
  - entry: theory0, 7 25
  - theory: theory2, linear, 4 -3
  - theory1 theory size 2
Data:
  - 1 obs 1
  - 2 obs 5
  - 11 obs 41
  - 6 obs 21
  - 7 obs 25
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; táxemésėhestȯtse form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory0 10 theory size
  - theory: theory0, ствал, 0 0
  - entry: theory0, 2 5
  - entry: theory0, 11 41
  - theory3 3 theory size
  - theory: theory1, square, 2 -6
  - theory2 3 theory size
  - entry: theory0, 1 1
  - entry: theory0, 6 21
  - theory: theory3, linear, 6 -1
  - entry: theory0, 7 25
  - theory: theory2, linear, 4 -3
  - theory1 2 theory size
Data:
  - 1 1 obs
  - 2 5 obs
  - 11 41 obs
  - 6 21 obs
  - 7 25 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; ствал y = entry(x) form.
Smallest lossless theory вуч?

The candidates are:
  - theory: theory2, linear, 5 and 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 and 105
  - entry: theory0, 12 and 149
  - entry: theory0, 0 and 5
  - theory3 theory size 2
  - theory: theory1, square, 5 and 3
  - theory: theory0, table, 0 and 0
  - entry: theory0, 8 and 69
  - theory: theory3, square, 7 and 5
  - theory2 theory size 3
  - entry: theory0, 11 and 126
The data are:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

Los candidatos son:
  - la teoría: theory2, linear, 5 y 1
  - theory0 el tamaño de la teoría 10
  - theory1 el tamaño de la teoría 2
  - la entrada: theory0, 10 y 105
  - la entrada: theory0, 12 y 149
  - la entrada: theory0, 0 y 5
  - theory3 el tamaño de la teoría 2
  - la teoría: theory1, square, 5 y 3
  - la teoría: theory0, mesa, 0 y 0
  - la entrada: theory0, 8 y 69
  - la teoría: theory3, square, 7 y 5
  - theory2 el tamaño de la teoría 3
  - la entrada: theory0, 11 y 126
Los datos son:
  - 0 la observación 5
  - 12 la observación 149
  - 10 la observación 105
  - 8 la observación 69
  - 11 la observación 126
Las reglas son:
  - la regla: a la teoría es lossless si y sólo si it predice every observation exactamente
  - la regla: choose el lossless la teoría de least tamaño
La semántica es: linear la forma y = p1 * x + p2; square la forma y = x * x + p2; constant la forma y = p2; la mesa la forma y = entry(x).
¿Qué smallest lossless la teoría?

候选项如下：
  - 的理论是：theory2、linear、5和1
  - theory0的理论规模是10
  - theory1的理论规模是2
  - 的条目是：theory0、10和105
  - 的条目是：theory0、12和149
  - 的条目是：theory0、0和5
  - theory3的理论规模是2
  - 的理论是：theory1、square、5和3
  - 的理论是：theory0、桌子、0和0
  - 的条目是：theory0、8和69
  - 的理论是：theory3、square、7和5
  - theory2的理论规模是3
  - 的条目是：theory0、11和126
数据如下：
  - 0观察到5
  - 12观察到149
  - 10观察到105
  - 8观察到69
  - 11观察到126
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

Adaylar:
  - kuram: theory2, linear, 5 ve 1
  - theory0 10 kuram boyut
  - theory1 2 kuram boyut
  - entry: theory0, 10 ve 105
  - entry: theory0, 12 ve 149
  - entry: theory0, 0 ve 5
  - theory3 2 kuram boyut
  - kuram: theory1, square, 5 ve 3
  - kuram: theory0, masa, 0 ve 0
  - entry: theory0, 8 ve 69
  - kuram: theory3, square, 7 ve 5
  - theory2 3 kuram boyut
  - entry: theory0, 11 ve 126
Veriler:
  - 0 5 obs
  - 12 149 obs
  - 10 105 obs
  - 8 69 obs
  - 11 126 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

Wagombea ni:
  - theory: theory2, linear, 5 na 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 na 105
  - entry: theory0, 12 na 149
  - entry: theory0, 0 na 5
  - theory3 theory size 2
  - theory: theory1, square, 5 na 3
  - theory: theory0, meza, 0 na 0
  - entry: theory0, 8 na 69
  - theory: theory3, square, 7 na 5
  - theory2 theory size 3
  - entry: theory0, 11 na 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

The candidates are:
  - theory: theory2, linear, 5 and 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 and 105
  - entry: theory0, 12 and 149
  - entry: theory0, 0 and 5
  - theory3 theory size 2
  - theory: theory1, square, 5 and 3
  - theory: theory0, table, 0 and 0
  - entry: theory0, 8 and 69
  - theory: theory3, square, 7 and 5
  - theory2 theory size 3
  - entry: theory0, 11 and 126
The data are:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

{candidates: [(theory theory2 linear 5 1) (theory_size theory0 10) (theory_size theory1 2) (entry theory0 10 105) (entry theory0 12 149) (entry theory0 0 5) (theory_size theory3 2) (theory theory1 square 5 3) (theory theory0 table 0 0) (entry theory0 8 69) (theory theory3 square 7 5) (theory_size theory2 3) (entry theory0 11 126)], data: [(obs 0 5) (obs 12 149) (obs 10 105) (obs 8 69) (obs 11 126)], query: smallest_lossless_theory, rules: [(rule (a_theory_is_lossless_iff_it_predicts_every_observation_exactly)) (rule (choose_the_lossless_theory_of_least_size))], semantics: [(form linear "y = p1 * x + p2") (form square "y = x * x + p2") (form constant "y = p2") (form table "y = entry(x)")]}

Die Kandidaten sind:
  - Theorie: theory2, linear, 5 und 1
  - theory0 Theorie Größe 10
  - theory1 Theorie Größe 2
  - Eintrag: theory0, 10 und 105
  - Eintrag: theory0, 12 und 149
  - Eintrag: theory0, 0 und 5
  - theory3 Theorie Größe 2
  - Theorie: theory1, square, 5 und 3
  - Theorie: theory0, Tisch, 0 und 0
  - Eintrag: theory0, 8 und 69
  - Theorie: theory3, square, 7 und 5
  - theory2 Theorie Größe 3
  - Eintrag: theory0, 11 und 126
Die Daten sind:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Die Regeln sind:
  - Regel ein Theorie werden verlustfrei gdw. er vorhersagen jeder Beobachtung genau
  - Regel wählen der verlustfrei Theorie aus geringst Größe
Die Semantik ist: linear formen y = p1 * x + p2; square formen y = x * x + p2; constant formen y = p2; der Tisch formen y = entry(x).
Was smallest verlustfrei Theorie?

Кандѝда̄т:
  - тѐо̄рија: theory2, linear, 5 и 1
  - theory0 тѐо̄рија величѝна 10
  - theory1 тѐо̄рија величѝна 2
  - одредница: theory0, 10 и 105
  - одредница: theory0, 12 и 149
  - одредница: theory0, 0 и 5
  - theory3 тѐо̄рија величѝна 2
  - тѐо̄рија: theory1, square, 5 и 3
  - тѐо̄рија: theory0, сто̑л, 0 и 0
  - одредница: theory0, 8 и 69
  - тѐо̄рија: theory3, square, 7 и 5
  - theory2 тѐо̄рија величѝна 3
  - одредница: theory0, 11 и 126
Податци:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Пра̏вило:
  - пра̏вило тѐо̄рија би̏ти lossless iff оно predvidjeti сва̏кӣ опа́жа̄ње тачно
  - пра̏вило изабрати lossless тѐо̄рија od minimalan величѝна
Сема̀нтика: linear oblik y = p1 * x + p2; square oblik y = x * x + p2; constant oblik y = p2; сто̑л oblik y = entry(x).
Smallest lossless тѐо̄рија kakav?

Ehdokkaat:
  - teoria: theory2, linear, 5 ja 1
  - theory0 teoria koko 10
  - theory1 teoria koko 2
  - artikkeli: theory0, 10 ja 105
  - artikkeli: theory0, 12 ja 149
  - artikkeli: theory0, 0 ja 5
  - theory3 teoria koko 2
  - teoria: theory1, square, 5 ja 3
  - teoria: theory0, pöytä, 0 ja 0
  - artikkeli: theory0, 8 ja 69
  - teoria: theory3, square, 7 ja 5
  - theory2 teoria koko 3
  - artikkeli: theory0, 11 ja 126
Tieto:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Säännöt:
  - sääntö teoria tulla häviötön joss se ennakoida jokainen havainnointi täsmälleen
  - sääntö valita häviötön teoria vaille vähin koko
Semantiikka: linear muotoilla y = p1 * x + p2; square muotoilla y = x * x + p2; constant muotoilla y = p2; pöytä muotoilla y = entry(x).
Mikä smallest häviötön teoria?

候选项如下：
  - 的理论是：theory2、linear、5和1
  - theory0的理论规模是10
  - theory1的理论规模是2
  - 的条目是：theory0、10和105
  - 的条目是：theory0、12和149
  - 的条目是：theory0、0和5
  - theory3的理论规模是2
  - 的理论是：theory1、square、5和3
  - 的理论是：theory0、桌子、0和0
  - 的条目是：theory0、8和69
  - 的理论是：theory3、square、7和5
  - theory2的理论规模是3
  - 的条目是：theory0、11和126
数据如下：
  - 0观察到5
  - 12观察到149
  - 10观察到105
  - 8观察到69
  - 11观察到126
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

候補者:
  - 理論:theory2, linear, 5と1
  - theory010理論大きさ
  - theory12理論大きさ
  - 項目:theory0, 10と105
  - 項目:theory0, 12と149
  - 項目:theory0, 0と5
  - theory32理論大きさ
  - 理論:theory1, square, 5と3
  - 理論:theory0, 台, 0と0
  - 項目:theory0, 8と69
  - 理論:theory3, square, 7と5
  - theory23理論大きさ
  - 項目:theory0, 11と126
資料:
  - 05obs
  - 12149obs
  - 10105obs
  - 869obs
  - 11126obs
規則:規則:理論れるロスレスiffこれ予言する凡ゆる観察正確に; 規則:選ぶロスレス理論の中の最小の大きさ.
意味論:lineary = p1 * x + p2形作る; squarey = x * x + p2形作る; constanty = p2形作る; 台y = entry(x)形作る.
smallestロスレス理論何と?

Adaylar:
  - kuram: theory2, linear, 5 ve 1
  - theory0 10 kuram boyut
  - theory1 2 kuram boyut
  - entry: theory0, 10 ve 105
  - entry: theory0, 12 ve 149
  - entry: theory0, 0 ve 5
  - theory3 2 kuram boyut
  - kuram: theory1, square, 5 ve 3
  - kuram: theory0, masa, 0 ve 0
  - entry: theory0, 8 ve 69
  - kuram: theory3, square, 7 ve 5
  - theory2 3 kuram boyut
  - entry: theory0, 11 ve 126
Veriler:
  - 0 5 obs
  - 12 149 obs
  - 10 105 obs
  - 8 69 obs
  - 11 126 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

مُرَشَّح:
  - نَظَرِيَّة: theory2، linear، 5 وَـ 1
  - نَظَرِيَّة مَقَاس theory0 10
  - نَظَرِيَّة مَقَاس theory1 2
  - مَدْخَل: theory0، 10 وَـ 105
  - مَدْخَل: theory0، 12 وَـ 149
  - مَدْخَل: theory0، 0 وَـ 5
  - نَظَرِيَّة مَقَاس theory3 2
  - نَظَرِيَّة: theory1، square، 5 وَـ 3
  - نَظَرِيَّة: theory0، طَاوِلَة، 0 وَـ 0
  - مَدْخَل: theory0، 8 وَـ 69
  - نَظَرِيَّة: theory3، square، 7 وَـ 5
  - نَظَرِيَّة مَقَاس theory2 3
  - مَدْخَل: theory0، 11 وَـ 126
بَيَانَات:
  - obs 0 5
  - obs 12 149
  - obs 10 105
  - obs 8 69
  - obs 11 126
قَانُون:
  - قَانُون نَظَرِيَّة كَانَ lossless iff هُوَ تَنَبَّأَ كُلّ رَصْد بِالضَّبْط
  - قَانُون اِخْتَارَ الـ lossless نَظَرِيَّة مِنْ أَقَلَّ مَقَاس
عِلْم اَلْمَعَانِي: شَكَّلَ linear y = p1 * x + p2؛ شَكَّلَ square y = x * x + p2؛ شَكَّلَ constant y = p2؛ شَكَّلَ الـ طَاوِلَة y = entry(x).
smallest lossless نَظَرِيَّة مَاذَا؟

Კანდიდატები:
  - თეორია: theory2, linear, 5 და 1
  - theory0 10 თეორია ზომა
  - theory1 2 თეორია ზომა
  - სასათაურო სიტყვა: theory0, 10 და 105
  - სასათაურო სიტყვა: theory0, 12 და 149
  - სასათაურო სიტყვა: theory0, 0 და 5
  - theory3 2 თეორია ზომა
  - თეორია: theory1, square, 5 და 3
  - თეორია: theory0, მაგიდა, 0 და 0
  - სასათაურო სიტყვა: theory0, 8 და 69
  - თეორია: theory3, square, 7 და 5
  - theory2 3 თეორია ზომა
  - სასათაურო სიტყვა: theory0, 11 და 126
Მონაცემები:
  - 0 5 obs
  - 12 149 obs
  - 10 105 obs
  - 8 69 obs
  - 11 126 obs
Წესი:
  - წესი თეორია ყოფნა უდანაკარგო iff ის predict ყველა დაკვირვება ზუსტად
  - წესი ამორჩევა უდანაკარგო თეორია of least ზომა
Სემანტიკა: linear y = p1 * x + p2 ბლანკი; square y = x * x + p2 ბლანკი; constant y = p2 ბლანკი; მაგიდა y = entry(x) ბლანკი.
Smallest უდანაკარგო თეორია რა?

Kaiwhakauru:
  - ariā: theory2, linear, 5 me 1
  - ariā size theory0 10
  - ariā size theory1 2
  - tāurunga: theory0, 10 me 105
  - tāurunga: theory0, 12 me 149
  - tāurunga: theory0, 0 me 5
  - ariā size theory3 2
  - ariā: theory1, square, 5 me 3
  - ariā: theory0, tēpu, 0 me 0
  - tāurunga: theory0, 8 me 69
  - ariā: theory3, square, 7 me 5
  - ariā size theory2 3
  - tāurunga: theory0, 11 me 126
Hōtuku:
  - obs 0 5
  - obs 12 149
  - obs 10 105
  - obs 8 69
  - obs 11 126
Rekureihana:
  - rekureihana ariā is lossless iff it matakite every observation pū
  - rekureihana whiri te lossless ariā o least size
Semantics: āhua linear y = p1 * x + p2; āhua square y = x * x + p2; āhua constant y = p2; āhua te tēpu y = entry(x).
Smallest lossless ariā unutai?

Candidates:
  - lý thuyết: theory2, linear, 5 và 1
  - theory0 lý thuyết kích thước 10
  - theory1 lý thuyết kích thước 2
  - mục từ: theory0, 10 và 105
  - mục từ: theory0, 12 và 149
  - mục từ: theory0, 0 và 5
  - theory3 lý thuyết kích thước 2
  - lý thuyết: theory1, square, 5 và 3
  - lý thuyết: theory0, bàn, 0 và 0
  - mục từ: theory0, 8 và 69
  - lý thuyết: theory3, square, 7 và 5
  - theory2 lý thuyết kích thước 3
  - mục từ: theory0, 11 và 126
Dữ liệu:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Quy tắc:
  - quy tắc lý thuyết được lossless iff nó dự báo mỗi observation đúng rồi
  - quy tắc chọn the lossless lý thuyết bằng least kích thước
Ngữ nghĩa: linear làm thành y = p1 * x + p2; square làm thành y = x * x + p2; constant làm thành y = p2; bàn làm thành y = entry(x).
Smallest lossless lý thuyết gì?

ผู้สมัคร:
  - ทฤษฎี:theory2, linear, 5และ1
  - theory0ทฤษฎีขนาด10
  - theory1ทฤษฎีขนาด2
  - entry:theory0, 10และ105
  - entry:theory0, 12และ149
  - entry:theory0, 0และ5
  - theory3ทฤษฎีขนาด2
  - ทฤษฎี:theory1, square, 5และ3
  - ทฤษฎี:theory0, โต๊ะ, 0และ0
  - entry:theory0, 8และ69
  - ทฤษฎี:theory3, square, 7และ5
  - theory2ทฤษฎีขนาด3
  - entry:theory0, 11และ126
ข้อมูล:
  - 0obs5
  - 12obs149
  - 10obs105
  - 8obs69
  - 11obs126
กฎ:กฎ:ทฤษฎีถูกlosslessiffมันทำนายทุกการสังเกตexactly; กฎ:เลือกlosslessทฤษฎีของleastขนาด.
อรรถศาสตร์:linearรูปร่างy = p1 * x + p2; squareรูปร่างy = x * x + p2; constantรูปร่างy = p2; โต๊ะรูปร่างy = entry(x).
smallestlosslessทฤษฎีอะไร?

வேட்பாளர்:
  - theory: theory2, linear, 5 மற்றும் 1
  - theory0 10 theory size
  - theory1 2 theory size
  - உள்நுழைவதற்கு அனுமதி: theory0, 10 மற்றும் 105
  - உள்நுழைவதற்கு அனுமதி: theory0, 12 மற்றும் 149
  - உள்நுழைவதற்கு அனுமதி: theory0, 0 மற்றும் 5
  - theory3 2 theory size
  - theory: theory1, square, 5 மற்றும் 3
  - theory: theory0, மேசை, 0 மற்றும் 0
  - உள்நுழைவதற்கு அனுமதி: theory0, 8 மற்றும் 69
  - theory: theory3, square, 7 மற்றும் 5
  - theory2 3 theory size
  - உள்நுழைவதற்கு அனுமதி: theory0, 11 மற்றும் 126
தரவுகள்:
  - 0 5 obs
  - 12 149 obs
  - 10 105 obs
  - 8 69 obs
  - 11 126 obs
rules: rule theory படு lossless iff it கணி ஒவ்வொரு observation exactly; rule choose lossless theory கொண்ட least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; மேசை y = entry(x) form.
smallest lossless theory என்ன?

Wagombea ni:
  - theory: theory2, linear, 5 na 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 na 105
  - entry: theory0, 12 na 149
  - entry: theory0, 0 na 5
  - theory3 theory size 2
  - theory: theory1, square, 5 na 3
  - theory: theory0, meza, 0 na 0
  - entry: theory0, 8 na 69
  - theory: theory3, square, 7 na 5
  - theory2 theory size 3
  - entry: theory0, 11 na 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

Candidates:
  - theory: theory2, linear, 5 dóó 1
  - theory0 10 theory size
  - theory1 2 theory size
  - entry: theory0, 10 dóó 105
  - entry: theory0, 12 dóó 149
  - entry: theory0, 0 dóó 5
  - theory3 2 theory size
  - theory: theory1, square, 5 dóó 3
  - theory: theory0, bikááʼ adání, 0 dóó 0
  - entry: theory0, 8 dóó 69
  - theory: theory3, square, 7 dóó 5
  - theory2 3 theory size
  - entry: theory0, 11 dóó 126
Data:
  - 0 5 obs
  - 12 149 obs
  - 10 105 obs
  - 8 69 obs
  - 11 126 obs
Bee hazʼáanii:
  - bee hazʼáanii theory átʼé lossless iff it predict every observation exactly
  - bee hazʼáanii choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; bikááʼ adání y = entry(x) form.
Smallest lossless theory haʼátʼíísh?

Candidates:
  - theory: theory2, linear, 5 aamma 1
  - theory0 10 theory size
  - theory1 2 theory size
  - entry: theory0, 10 aamma 105
  - entry: theory0, 12 aamma 149
  - entry: theory0, 0 aamma 5
  - theory3 2 theory size
  - theory: theory1, square, 5 aamma 3
  - theory: theory0, table, 0 aamma 0
  - entry: theory0, 8 aamma 69
  - theory: theory3, square, 7 aamma 5
  - theory2 3 theory size
  - entry: theory0, 11 aamma 126
Data:
  - 0 5 obs
  - 12 149 obs
  - 10 105 obs
  - 8 69 obs
  - 11 126 obs
Rules: rule theory a lossless iff una predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 blanketti; square y = x * x + p2 blanketti; constant y = p2 blanketti; table y = entry(x) blanketti.
Smallest lossless theory what?

Candidates:
  - theory: theory2, linear, 5 na 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 na 105
  - entry: theory0, 12 na 149
  - entry: theory0, 0 na 5
  - theory3 theory size 2
  - theory: theory1, square, 5 na 3
  - theory: theory0, table, 0 na 0
  - entry: theory0, 8 na 69
  - theory: theory3, square, 7 na 5
  - theory2 theory size 3
  - entry: theory0, 11 na 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory bilong least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory2, linear, 5 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 105
  - entry: theory0, 12 149
  - entry: theory0, 0 5
  - theory3 theory size 2
  - theory: theory1, square, 5 3
  - theory: theory0, table, 0 0
  - entry: theory0, 8 69
  - theory: theory3, square, 7 5
  - theory2 theory size 3
  - entry: theory0, 11 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Nikanixi:
  - nikanixi theory is lossless iff it predict every observation exactly
  - nikanixi choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory kwèch?

Candidates:
  - theory: theory2, linear, 5 а 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 а 105
  - entry: theory0, 12 а 149
  - entry: theory0, 0 а 5
  - theory3 theory size 2
  - theory: theory1, square, 5 а 3
  - theory: theory0, table, 0 а 0
  - entry: theory0, 8 а 69
  - theory: theory3, square, 7 а 5
  - theory2 theory size 3
  - entry: theory0, 11 а 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Rules:
  - rule theory хила lossless iff it predict дерриг observation exactly
  - rule хержа lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory фу?

후보자:
  - 이론: theory2, linear, 5 1
  - theory0 10 이론 크기
  - theory1 2 이론 크기
  - 항목: theory0, 10 105
  - 항목: theory0, 12 149
  - 항목: theory0, 0 5
  - theory3 2 이론 크기
  - 이론: theory1, square, 5 3
  - 이론: theory0, 테이블, 0 0
  - 항목: theory0, 8 69
  - 이론: theory3, square, 7 5
  - theory2 3 이론 크기
  - 항목: theory0, 11 126
자료:
  - 0 5 obs
  - 12 149 obs
  - 10 105 obs
  - 8 69 obs
  - 11 126 obs
규칙: 규칙 이론 is lossless iff 이것 예언하다 각 관찰 정확하게; 규칙 고르다 lossless 이론...의 가장 적게 크기.
의미론: linear y = p1 * x + p2 형상; square y = x * x + p2 형상; constant y = p2 형상; 테이블 y = entry(x) 형상.
smallest lossless 이론 무엇?

Kandidatu:
  - theory: theory2, linear, 5 eta 1
  - theory0 10 theory tamaina
  - theory1 2 theory tamaina
  - sarrera: theory0, 10 eta 105
  - sarrera: theory0, 12 eta 149
  - sarrera: theory0, 0 eta 5
  - theory3 2 theory tamaina
  - theory: theory1, square, 5 eta 3
  - theory: theory0, mahai, 0 eta 0
  - sarrera: theory0, 8 eta 69
  - theory: theory3, square, 7 eta 5
  - theory2 3 theory tamaina
  - sarrera: theory0, 11 eta 126
Data:
  - 0 5 obs
  - 12 149 obs
  - 10 105 obs
  - 8 69 obs
  - 11 126 obs
Arau:
  - arau bat theory izan lossless iff it aurresan every observation exactly
  - arau aukeratu the lossless theory of least tamaina
Semantics: linear y = p1 * x + p2 forma; square y = x * x + p2 forma; constant y = p2 forma; mahai y = entry(x) forma.
Smallest lossless theory zer?

ᎠᏙᎩᏯᏍᎩ:
  - theory: theory2, linear, 5 ᎠᎴ 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 ᎠᎴ 105
  - entry: theory0, 12 ᎠᎴ 149
  - entry: theory0, 0 ᎠᎴ 5
  - theory3 theory size 2
  - theory: theory1, square, 5 ᎠᎴ 3
  - theory: theory0, ᎦᏍᎩᎶ, 0 ᎠᎴ 0
  - entry: theory0, 8 ᎠᎴ 69
  - theory: theory3, square, 7 ᎠᎴ 5
  - theory2 theory size 3
  - entry: theory0, 11 ᎠᎴ 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ᎦᏍᎩᎶ form y = entry(x).
What smallest lossless theory?

Candidates:
  - theory: theory2, linear, 5 1
  - theory0 theory chhika 10
  - theory1 theory chhika 2
  - entry: theory0, 10 105
  - entry: theory0, 12 149
  - entry: theory0, 0 5
  - theory3 theory chhika 2
  - theory: theory1, square, 5 3
  - theory: theory0, patacha, 0 0
  - entry: theory0, 8 69
  - theory: theory3, square, 7 5
  - theory2 theory chhika 3
  - entry: theory0, 11 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Rules:
  - rule theory tiyay lossless iff it predict tukuy observation exactly
  - rule akllay lossless theory of least chhika
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; patacha form y = entry(x).
Smallest lossless theory what?

Candidates:
  - тиориэ: theory2, linear, 5 ыкӏи 1
  - theory0 10 тиориэ size
  - theory1 2 тиориэ size
  - entry: theory0, 10 ыкӏи 105
  - entry: theory0, 12 ыкӏи 149
  - entry: theory0, 0 ыкӏи 5
  - theory3 2 тиориэ size
  - тиориэ: theory1, square, 5 ыкӏи 3
  - тиориэ: theory0, table, 0 ыкӏи 0
  - entry: theory0, 8 ыкӏи 69
  - тиориэ: theory3, square, 7 ыкӏи 5
  - theory2 3 тиориэ size
  - entry: theory0, 11 ыкӏи 126
Data:
  - 0 5 obs
  - 12 149 obs
  - 10 105 obs
  - 8 69 obs
  - 11 126 obs
Rules: rule тиориэ is lossless iff it predict every observation exactly; rule choose the lossless тиориэ of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless тиориэ сыд?

Candidates:
  - theory: theory2, linear, 5 thiab 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 thiab 105
  - entry: theory0, 12 thiab 149
  - entry: theory0, 0 thiab 5
  - theory3 theory size 2
  - theory: theory1, square, 5 thiab 3
  - theory: theory0, rooj, 0 thiab 0
  - entry: theory0, 8 thiab 69
  - theory: theory3, square, 7 thiab 5
  - theory2 theory size 3
  - entry: theory0, 11 thiab 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Cai: cai theory is lossless iff nws predict every observation exactly; cai choose lossless theory of least size.
Lub ntsiab: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; rooj form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory2, linear, 5 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 105
  - entry: theory0, 12 149
  - entry: theory0, 0 5
  - theory3 theory size 2
  - theory: theory1, square, 5 3
  - theory: theory0, table, 0 0
  - entry: theory0, 8 69
  - theory: theory3, square, 7 5
  - theory2 theory size 3
  - entry: theory0, 11 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of wy krook size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory ining-jak?

Candidates:
  - theory: theory2, linear, 5 micha' 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 micha' 105
  - entry: theory0, 12 micha' 149
  - entry: theory0, 0 micha' 5
  - theory3 theory size 2
  - theory: theory1, square, 5 micha' 3
  - theory: theory0, table, 0 micha' 0
  - entry: theory0, 8 micha' 69
  - theory: theory3, square, 7 micha' 5
  - theory2 theory size 3
  - entry: theory0, 11 micha' 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory nanta?

Candidates:
  - theory: theory2, linear, 5 カ 1
  - theory0 10 theory size
  - theory1 2 theory size
  - entry: theory0, 10 カ 105
  - entry: theory0, 12 カ 149
  - entry: theory0, 0 カ 5
  - theory3 2 theory size
  - theory: theory1, square, 5 カ 3
  - theory: theory0, table, 0 カ 0
  - entry: theory0, 8 カ 69
  - theory: theory3, square, 7 カ 5
  - theory2 3 theory size
  - entry: theory0, 11 カ 126
Data:
  - 0 5 obs
  - 12 149 obs
  - 10 105 obs
  - 8 69 obs
  - 11 126 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 ノカ; square y = x * x + p2 ノカ; constant y = p2 ノカ; table y = entry(x) ノカ.
Smallest lossless theory what?

Candidates:
  - theory: theory2, linear, 5 ынкъам 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 ынкъам 105
  - entry: theory0, 12 ынкъам 149
  - entry: theory0, 0 ынкъам 5
  - theory3 theory size 2
  - theory: theory1, square, 5 ынкъам 3
  - theory: theory0, table, 0 ынкъам 0
  - entry: theory0, 8 ынкъам 69
  - theory: theory3, square, 7 ынкъам 5
  - theory2 theory size 3
  - entry: theory0, 11 ынкъам 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory2, linear, 5 yéetel 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 yéetel 105
  - entry: theory0, 12 yéetel 149
  - entry: theory0, 0 yéetel 5
  - theory3 theory size 2
  - theory: theory1, square, 5 yéetel 3
  - theory: theory0, table, 0 yéetel 0
  - entry: theory0, 8 yéetel 69
  - theory: theory3, square, 7 yéetel 5
  - theory2 theory size 3
  - entry: theory0, 11 yéetel 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Rules:
  - rule theory yan lossless iff it predict every observation exactly
  - rule yéey lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory2, linear, 5 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 105
  - entry: theory0, 12 149
  - entry: theory0, 0 5
  - theory3 theory size 2
  - theory: theory1, square, 5 3
  - theory: theory0, mę́soną, 0 0
  - entry: theory0, 8 69
  - theory: theory3, square, 7 5
  - theory2 theory size 3
  - entry: theory0, 11 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Rules:
  - rule theory is lossless iff ą́wąną predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mę́soną form y = entry(x).
Smallest lossless theory híli?

Candidates:
  - theory: theory2, linear, 5 na 1
  - theory0 10 theory size
  - theory1 2 theory size
  - entry: theory0, 10 na 105
  - entry: theory0, 12 na 149
  - entry: theory0, 0 na 5
  - theory3 2 theory size
  - theory: theory1, square, 5 na 3
  - theory: theory0, table, 0 na 0
  - entry: theory0, 8 na 69
  - theory: theory3, square, 7 na 5
  - theory2 3 theory size
  - entry: theory0, 11 na 126
Data:
  - 0 5 obs
  - 12 149 obs
  - 10 105 obs
  - 8 69 obs
  - 11 126 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory2, linear, 5 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 105
  - entry: theory0, 12 149
  - entry: theory0, 0 5
  - theory3 theory size 2
  - theory: theory1, square, 5 3
  - theory: theory0, table, 0 0
  - entry: theory0, 8 69
  - theory: theory3, square, 7 5
  - theory2 theory size 3
  - entry: theory0, 11 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory2, linear, 5 1
  - theory0 10 theory size
  - theory1 2 theory size
  - entry: theory0, 10 105
  - entry: theory0, 12 149
  - entry: theory0, 0 5
  - theory3 2 theory size
  - theory: theory1, square, 5 3
  - theory: theory0, table, 0 0
  - entry: theory0, 8 69
  - theory: theory3, square, 7 5
  - theory2 3 theory size
  - entry: theory0, 11 126
Data:
  - 0 5 obs
  - 12 149 obs
  - 10 105 obs
  - 8 69 obs
  - 11 126 obs
Rules:
  - rule maya theory is lossless iff it predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory2, linear, 5 ǂʻá 1
  - theory0 theory ʻǁnàhã 10
  - theory1 theory ʻǁnàhã 2
  - entry: theory0, 10 ǂʻá 105
  - entry: theory0, 12 ǂʻá 149
  - entry: theory0, 0 ǂʻá 5
  - theory3 theory ʻǁnàhã 2
  - theory: theory1, square, 5 ǂʻá 3
  - theory: theory0, table, 0 ǂʻá 0
  - entry: theory0, 8 ǂʻá 69
  - theory: theory3, square, 7 ǂʻá 5
  - theory2 theory ʻǁnàhã 3
  - entry: theory0, 11 ǂʻá 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Rules:
  - rule theory ǀîi lossless iff èh predict every observation exactly
  - rule choose lossless theory of least ʻǁnàhã
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory2, linear, 5 1
  - theory0 10 theory size
  - theory1 2 theory size
  - entry: theory0, 10 105
  - entry: theory0, 12 149
  - entry: theory0, 0 5
  - theory3 2 theory size
  - theory: theory1, square, 5 3
  - theory: theory0, остол, 0 0
  - entry: theory0, 8 69
  - theory: theory3, square, 7 5
  - theory2 3 theory size
  - entry: theory0, 11 126
Data:
  - 0 5 obs
  - 12 149 obs
  - 10 105 obs
  - 8 69 obs
  - 11 126 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; остол y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory2, linear, 5 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 105
  - entry: theory0, 12 149
  - entry: theory0, 0 5
  - theory3 theory size 2
  - theory: theory1, square, 5 3
  - theory: theory0, table, 0 0
  - entry: theory0, 8 69
  - theory: theory3, square, 7 5
  - theory2 theory size 3
  - entry: theory0, 11 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory2, linear, 5 1
  - theory0 10 theory size
  - theory1 2 theory size
  - entry: theory0, 10 105
  - entry: theory0, 12 149
  - entry: theory0, 0 5
  - theory3 2 theory size
  - theory: theory1, square, 5 3
  - theory: theory0, table, 0 0
  - entry: theory0, 8 69
  - theory: theory3, square, 7 5
  - theory2 3 theory size
  - entry: theory0, 11 126
Data:
  - 0 5 obs
  - 12 149 obs
  - 10 105 obs
  - 8 69 obs
  - 11 126 obs
Rules:
  - rule theory is lossless iff kitu predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory2, linear, 5 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 105
  - entry: theory0, 12 149
  - entry: theory0, 0 5
  - theory3 theory size 2
  - theory: theory1, square, 5 3
  - theory: theory0, mesa, 0 0
  - entry: theory0, 8 69
  - theory: theory3, square, 7 5
  - theory2 theory size 3
  - entry: theory0, 11 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mesa form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory2, linear, 5 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 105
  - entry: theory0, 12 149
  - entry: theory0, 0 5
  - theory3 theory size 2
  - theory: theory1, square, 5 3
  - theory: theory0, table, 0 0
  - entry: theory0, 8 69
  - theory: theory3, square, 7 5
  - theory2 theory size 3
  - entry: theory0, 11 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Rules:
  - rule theory nemi lossless iff yaja predict every observation exactly
  - rule choose ne lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ne table form y = entry(x).
Smallest lossless theory tay?

Les candidats sont:
  - théorie: theory2, linear, 5 et 1
  - theory0 théorie taille 10
  - theory1 théorie taille 2
  - article: theory0, 10 et 105
  - article: theory0, 12 et 149
  - article: theory0, 0 et 5
  - theory3 théorie taille 2
  - théorie: theory1, square, 5 et 3
  - théorie: theory0, table, 0 et 0
  - article: theory0, 8 et 69
  - théorie: theory3, square, 7 et 5
  - theory2 théorie taille 3
  - article: theory0, 11 et 126
Les données sont:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Les règles sont:
  - règle un théorie être lossless ssi il prédire tout observation exactement
  - règle choisir le lossless théorie du moindre taille
La sémantique est : linear former y = p1 * x + p2 ; square former y = x * x + p2 ; constant former y = p2 ; la table former y = entry(x).
Quoi smallest lossless théorie ?

Kandidato:
  - teorio: theory2, linear, 5 kaj 1
  - theory0 teorio grandeco 10
  - theory1 teorio grandeco 2
  - entry: theory0, 10 kaj 105
  - entry: theory0, 12 kaj 149
  - entry: theory0, 0 kaj 5
  - theory3 teorio grandeco 2
  - teorio: theory1, square, 5 kaj 3
  - teorio: theory0, tablo, 0 kaj 0
  - entry: theory0, 8 kaj 69
  - teorio: theory3, square, 7 kaj 5
  - theory2 teorio grandeco 3
  - entry: theory0, 11 kaj 126
Datumo:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Regulo: regulo teorio egali lossless iff ĝi predict ĉiu observo ekzakte; regulo elekti lossless teorio de plej malmulta grandeco.
Semantics: linear formi y = p1 * x + p2; square formi y = x * x + p2; constant formi y = p2; tablo formi y = entry(x).
Smallest lossless teorio kio?

Indulók:
  - elmélet: theory2, linear, 5 és 1
  - theory0 elmélet méret 10
  - theory1 elmélet méret 2
  - szócikk: theory0, 10 és 105
  - szócikk: theory0, 12 és 149
  - szócikk: theory0, 0 és 5
  - theory3 elmélet méret 2
  - elmélet: theory1, square, 5 és 3
  - elmélet: theory0, asztal, 0 és 0
  - szócikk: theory0, 8 és 69
  - elmélet: theory3, square, 7 és 5
  - theory2 elmélet méret 3
  - szócikk: theory0, 11 és 126
Adat:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Szabályok:
  - szabály elmélet van veszteségmentes acsa az megjósol minden megfigyelés pontosan
  - szabály kiválaszt a veszteségmentes elmélet of legkisebb méret
Szemantika: linear kialakít y = p1 * x + p2; square kialakít y = x * x + p2; constant kialakít y = p2; a asztal kialakít y = entry(x).
Smallest veszteségmentes elmélet melyik?

候選人:
  - theory:theory2, linear, 5及1
  - theory0theory size10
  - theory1theory size2
  - entry:theory0, 10及105
  - entry:theory0, 12及149
  - entry:theory0, 0及5
  - theory3theory size2
  - theory:theory1, square, 5及3
  - theory:theory0, 檯, 0及0
  - entry:theory0, 8及69
  - theory:theory3, square, 7及5
  - theory2theory size3
  - entry:theory0, 11及126
數據:
  - 0obs5
  - 12obs149
  - 10obs105
  - 8obs69
  - 11obs126
rules:rule:一theory是losslessiffitpredict每observationexactly; rule:揀losslesstheory...嘅leastsize.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; 檯formy = entry(x).
smallest lossless theory乜嘢?

Candidates:
  - theory: theory2, linear, 5 とぅ 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 とぅ 105
  - entry: theory0, 12 とぅ 149
  - entry: theory0, 0 とぅ 5
  - theory3 theory size 2
  - theory: theory1, square, 5 とぅ 3
  - theory: theory0, table, 0 とぅ 0
  - entry: theory0, 8 とぅ 69
  - theory: theory3, square, 7 とぅ 5
  - theory2 theory size 3
  - entry: theory0, 11 とぅ 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Rules: rule theory 有ん lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Үміткер:
  - теория: theory2, linear, 5 және 1
  - theory0 теория мөлшер 10
  - theory1 теория мөлшер 2
  - entry: theory0, 10 және 105
  - entry: theory0, 12 және 149
  - entry: theory0, 0 және 5
  - theory3 теория мөлшер 2
  - теория: theory1, square, 5 және 3
  - теория: theory0, үстел, 0 және 0
  - entry: theory0, 8 және 69
  - теория: theory3, square, 7 және 5
  - theory2 теория мөлшер 3
  - entry: theory0, 11 және 126
Деректер:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Ереже: ереже теория is lossless iff ол predict әр бақылау exactly; ереже таңдау lossless теория туралы least мөлшер.
Семантикалық: linear пішін y = p1 * x + p2; square пішін y = x * x + p2; constant пішін y = p2; үстел пішін y = entry(x).
Smallest lossless теория не?

מועמדת:
  - תּוֹרָה: theory2, linear, 5 וְ־ 1
  - theory0 תּוֹרָה גֹּדֶל 10
  - theory1 תּוֹרָה גֹּדֶל 2
  - entry: theory0, 10 וְ־ 105
  - entry: theory0, 12 וְ־ 149
  - entry: theory0, 0 וְ־ 5
  - theory3 תּוֹרָה גֹּדֶל 2
  - תּוֹרָה: theory1, square, 5 וְ־ 3
  - תּוֹרָה: theory0, טַבְלָה, 0 וְ־ 0
  - entry: theory0, 8 וְ־ 69
  - תּוֹרָה: theory3, square, 7 וְ־ 5
  - theory2 תּוֹרָה גֹּדֶל 3
  - entry: theory0, 11 וְ־ 126
נְתוּנִים:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
מָשַׁל:
  - מָשַׁל אַחַת תּוֹרָה הוא lossless אםם זֶה predict כֹּל תַּצְפִּית בדיוק
  - מָשַׁל בחר ה־ lossless תּוֹרָה שֶׁל least גֹּדֶל
תורת המשמעים: linear צורה y = p1 * x + p2; square צורה y = x * x + p2; constant צורה y = p2; טַבְלָה ה־ צורה y = entry(x).
איזה smallest lossless תּוֹרָה?

Candidates:
  - theory: theory2, linear, 5 დო 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 დო 105
  - entry: theory0, 12 დო 149
  - entry: theory0, 0 დო 5
  - theory3 theory size 2
  - theory: theory1, square, 5 დო 3
  - theory: theory0, table, 0 დო 0
  - entry: theory0, 8 დო 69
  - theory: theory3, square, 7 დო 5
  - theory2 theory size 3
  - entry: theory0, 11 დო 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Kandidat:
  - teori: theory2, linear, 5 dan 1
  - theory0 teori ukuran 10
  - theory1 teori ukuran 2
  - lema: theory0, 10 dan 105
  - lema: theory0, 12 dan 149
  - lema: theory0, 0 dan 5
  - theory3 teori ukuran 2
  - teori: theory1, square, 5 dan 3
  - teori: theory0, meja, 0 dan 0
  - lema: theory0, 8 dan 69
  - teori: theory3, square, 7 dan 5
  - theory2 teori ukuran 3
  - lema: theory0, 11 dan 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Rules:
  - rule teori berada lossless iff it predict setiap observation tepat
  - rule memilih si lossless teori dari least ukuran
Semantik: linear formulir y = p1 * x + p2; square formulir y = x * x + p2; constant formulir y = p2; meja si formulir y = entry(x).
Smallest lossless teori apa?

បេក្ខជន:
  - ទ្រឹស្ដី:theory2, linear, 5នឹង1
  - theory0ទ្រឹស្ដីទំហំ10
  - theory1ទ្រឹស្ដីទំហំ2
  - មេពាក្យ:theory0, 10នឹង105
  - មេពាក្យ:theory0, 12នឹង149
  - មេពាក្យ:theory0, 0នឹង5
  - theory3ទ្រឹស្ដីទំហំ2
  - ទ្រឹស្ដី:theory1, square, 5នឹង3
  - ទ្រឹស្ដី:theory0, តុ, 0នឹង0
  - មេពាក្យ:theory0, 8នឹង69
  - ទ្រឹស្ដី:theory3, square, 7នឹង5
  - theory2ទ្រឹស្ដីទំហំ3
  - មេពាក្យ:theory0, 11នឹង126
ទិន្នន័យ:
  - 0obs5
  - 12obs149
  - 10obs105
  - 8obs69
  - 11obs126
ក្បួន:ក្បួន:ទ្រឹស្ដីត្រូវបានlosslessiffវាចាប់យាមរាល់គំនន់exactly; ក្បួន:រើសthelosslessទ្រឹស្ដីនៃleastទំហំ.
និឃណ្ដសាស្ត្រ:linearគ្រោងy = p1 * x + p2; squareគ្រោងy = x * x + p2; constantគ្រោងy = p2; តុគ្រោងy = entry(x).
smallestlosslessទ្រឹស្ដីអី?

ຜູ້ສະໝັກ:
  - ທິດສະດີ:theory2, linear, 5ແລະ1
  - theory0ທິດສະດີຂະຫນາດ10
  - theory1ທິດສະດີຂະຫນາດ2
  - entry:theory0, 10ແລະ105
  - entry:theory0, 12ແລະ149
  - entry:theory0, 0ແລະ5
  - theory3ທິດສະດີຂະຫນາດ2
  - ທິດສະດີ:theory1, square, 5ແລະ3
  - ທິດສະດີ:theory0, ໂຕະ, 0ແລະ0
  - entry:theory0, 8ແລະ69
  - ທິດສະດີ:theory3, square, 7ແລະ5
  - theory2ທິດສະດີຂະຫນາດ3
  - entry:theory0, 11ແລະ126
ຂໍ້ມູນ:
  - 0obs5
  - 12obs149
  - 10obs105
  - 8obs69
  - 11obs126
ກະຕິກາ:ກະຕິກາ:ທິດສະດີຢູ່losslessiffມັນທຳນວາຍທຸກobservationexactly; ກະຕິກາ:ເລືອກlosslessທິດສະດີຂອງleastຂະຫນາດ.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; ໂຕະformy = entry(x).
smallestlosslessທິດສະດີຫຍັງ?

candidates:
  - theory: theory2, linear, 5 మరియు 1
  - theory0 10 theory size
  - theory1 2 theory size
  - entry: theory0, 10 మరియు 105
  - entry: theory0, 12 మరియు 149
  - entry: theory0, 0 మరియు 5
  - theory3 2 theory size
  - theory: theory1, square, 5 మరియు 3
  - theory: theory0, బల్ల, 0 మరియు 0
  - entry: theory0, 8 మరియు 69
  - theory: theory3, square, 7 మరియు 5
  - theory2 3 theory size
  - entry: theory0, 11 మరియు 126
data:
  - 0 5 obs
  - 12 149 obs
  - 10 105 obs
  - 8 69 obs
  - 11 126 obs
నియమం: నియమం theory ఉండు lossless iff it predict ప్రతి పరిశీలన exactly; నియమం choose lossless theory of least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; బల్ల y = entry(x) form.
smallest lossless theory ఏమిటి?

Candidates:
  - theory: theory2, linear, 5 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 105
  - entry: theory0, 12 149
  - entry: theory0, 0 5
  - theory3 theory size 2
  - theory: theory1, square, 5 3
  - theory: theory0, table, 0 0
  - entry: theory0, 8 69
  - theory: theory3, square, 7 5
  - theory2 theory size 3
  - entry: theory0, 11 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Rules: rule theory wà lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
What smallest lossless theory?

Candidates:
  - theory: theory2, linear, 5 1
  - theory0 10 theory size
  - theory1 2 theory size
  - entry: theory0, 10 105
  - entry: theory0, 12 149
  - entry: theory0, 0 5
  - theory3 2 theory size
  - theory: theory1, square, 5 3
  - theory: theory0, table, 0 0
  - entry: theory0, 8 69
  - theory: theory3, square, 7 5
  - theory2 3 theory size
  - entry: theory0, 11 126
Data:
  - 0 5 obs
  - 12 149 obs
  - 10 105 obs
  - 8 69 obs
  - 11 126 obs
Rules:
  - rule theory naiágúóli lossless iff it predict every observation exactly
  - rule choose the lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

candidates:
  - theory: theory2, linear, 5 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 105
  - entry: theory0, 12 149
  - entry: theory0, 0 5
  - theory3 theory size 2
  - theory: theory1, square, 5 3
  - theory: theory0, table, 0 0
  - entry: theory0, 8 69
  - theory: theory3, square, 7 5
  - theory2 theory size 3
  - entry: theory0, 11 126
data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
smallest lossless theory what?

Candidates:
  - theory: theory2, linear, 5 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 105
  - entry: theory0, 12 149
  - entry: theory0, 0 5
  - theory3 theory size 2
  - theory: theory1, square, 5 3
  - theory: theory0, tafra, 0 0
  - entry: theory0, 8 69
  - theory: theory3, square, 7 5
  - theory2 theory size 3
  - entry: theory0, 11 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; tafra form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory2, linear, 5 1
  - theory0 theory size 10
  - theory1 theory size 2
  - entry: theory0, 10 105
  - entry: theory0, 12 149
  - entry: theory0, 0 5
  - theory3 theory size 2
  - theory: theory1, square, 5 3
  - theory: theory0, táxemésėhestȯtse, 0 0
  - entry: theory0, 8 69
  - theory: theory3, square, 7 5
  - theory2 theory size 3
  - entry: theory0, 11 126
Data:
  - 0 obs 5
  - 12 obs 149
  - 10 obs 105
  - 8 obs 69
  - 11 obs 126
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; táxemésėhestȯtse form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory2, linear, 5 1
  - theory0 10 theory size
  - theory1 2 theory size
  - entry: theory0, 10 105
  - entry: theory0, 12 149
  - entry: theory0, 0 5
  - theory3 2 theory size
  - theory: theory1, square, 5 3
  - theory: theory0, ствал, 0 0
  - entry: theory0, 8 69
  - theory: theory3, square, 7 5
  - theory2 3 theory size
  - entry: theory0, 11 126
Data:
  - 0 5 obs
  - 12 149 obs
  - 10 105 obs
  - 8 69 obs
  - 11 126 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; ствал y = entry(x) form.
Smallest lossless theory вуч?

The candidates are:
  - theory: theory1, linear, 6 and 0
  - entry: theory2, 0 and 2
  - entry: theory2, 9 and 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 and 5
  - theory: theory3, linear, 5 and 2
  - theory1 theory size 3
  - theory: theory2, table, 0 and 0
  - theory3 theory size 3
  - entry: theory2, 7 and 37
  - entry: theory2, 12 and 62
  - entry: theory2, 2 and 12
The data are:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

Los candidatos son:
  - la teoría: theory1, linear, 6 y 0
  - la entrada: theory2, 0 y 2
  - la entrada: theory2, 9 y 47
  - theory2 el tamaño de la teoría 10
  - theory0 el tamaño de la teoría 2
  - la teoría: theory0, square, 7 y 5
  - la teoría: theory3, linear, 5 y 2
  - theory1 el tamaño de la teoría 3
  - la teoría: theory2, mesa, 0 y 0
  - theory3 el tamaño de la teoría 3
  - la entrada: theory2, 7 y 37
  - la entrada: theory2, 12 y 62
  - la entrada: theory2, 2 y 12
Los datos son:
  - 2 la observación 12
  - 12 la observación 62
  - 7 la observación 37
  - 0 la observación 2
  - 9 la observación 47
Las reglas son:
  - la regla: a la teoría es lossless si y sólo si it predice every observation exactamente
  - la regla: choose el lossless la teoría de least tamaño
La semántica es: linear la forma y = p1 * x + p2; square la forma y = x * x + p2; constant la forma y = p2; la mesa la forma y = entry(x).
¿Qué smallest lossless la teoría?

候选项如下：
  - 的理论是：theory1、linear、6和0
  - 的条目是：theory2、0和2
  - 的条目是：theory2、9和47
  - theory2的理论规模是10
  - theory0的理论规模是2
  - 的理论是：theory0、square、7和5
  - 的理论是：theory3、linear、5和2
  - theory1的理论规模是3
  - 的理论是：theory2、桌子、0和0
  - theory3的理论规模是3
  - 的条目是：theory2、7和37
  - 的条目是：theory2、12和62
  - 的条目是：theory2、2和12
数据如下：
  - 2观察到12
  - 12观察到62
  - 7观察到37
  - 0观察到2
  - 9观察到47
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

Adaylar:
  - kuram: theory1, linear, 6 ve 0
  - entry: theory2, 0 ve 2
  - entry: theory2, 9 ve 47
  - theory2 10 kuram boyut
  - theory0 2 kuram boyut
  - kuram: theory0, square, 7 ve 5
  - kuram: theory3, linear, 5 ve 2
  - theory1 3 kuram boyut
  - kuram: theory2, masa, 0 ve 0
  - theory3 3 kuram boyut
  - entry: theory2, 7 ve 37
  - entry: theory2, 12 ve 62
  - entry: theory2, 2 ve 12
Veriler:
  - 2 12 obs
  - 12 62 obs
  - 7 37 obs
  - 0 2 obs
  - 9 47 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

Wagombea ni:
  - theory: theory1, linear, 6 na 0
  - entry: theory2, 0 na 2
  - entry: theory2, 9 na 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 na 5
  - theory: theory3, linear, 5 na 2
  - theory1 theory size 3
  - theory: theory2, meza, 0 na 0
  - theory3 theory size 3
  - entry: theory2, 7 na 37
  - entry: theory2, 12 na 62
  - entry: theory2, 2 na 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

The candidates are:
  - theory: theory1, linear, 6 and 0
  - entry: theory2, 0 and 2
  - entry: theory2, 9 and 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 and 5
  - theory: theory3, linear, 5 and 2
  - theory1 theory size 3
  - theory: theory2, table, 0 and 0
  - theory3 theory size 3
  - entry: theory2, 7 and 37
  - entry: theory2, 12 and 62
  - entry: theory2, 2 and 12
The data are:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

{candidates: [(theory theory1 linear 6 0) (entry theory2 0 2) (entry theory2 9 47) (theory_size theory2 10) (theory_size theory0 2) (theory theory0 square 7 5) (theory theory3 linear 5 2) (theory_size theory1 3) (theory theory2 table 0 0) (theory_size theory3 3) (entry theory2 7 37) (entry theory2 12 62) (entry theory2 2 12)], data: [(obs 2 12) (obs 12 62) (obs 7 37) (obs 0 2) (obs 9 47)], query: smallest_lossless_theory, rules: [(rule (a_theory_is_lossless_iff_it_predicts_every_observation_exactly)) (rule (choose_the_lossless_theory_of_least_size))], semantics: [(form linear "y = p1 * x + p2") (form square "y = x * x + p2") (form constant "y = p2") (form table "y = entry(x)")]}

Die Kandidaten sind:
  - Theorie: theory1, linear, 6 und 0
  - Eintrag: theory2, 0 und 2
  - Eintrag: theory2, 9 und 47
  - theory2 Theorie Größe 10
  - theory0 Theorie Größe 2
  - Theorie: theory0, square, 7 und 5
  - Theorie: theory3, linear, 5 und 2
  - theory1 Theorie Größe 3
  - Theorie: theory2, Tisch, 0 und 0
  - theory3 Theorie Größe 3
  - Eintrag: theory2, 7 und 37
  - Eintrag: theory2, 12 und 62
  - Eintrag: theory2, 2 und 12
Die Daten sind:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Die Regeln sind:
  - Regel ein Theorie werden verlustfrei gdw. er vorhersagen jeder Beobachtung genau
  - Regel wählen der verlustfrei Theorie aus geringst Größe
Die Semantik ist: linear formen y = p1 * x + p2; square formen y = x * x + p2; constant formen y = p2; der Tisch formen y = entry(x).
Was smallest verlustfrei Theorie?

Кандѝда̄т:
  - тѐо̄рија: theory1, linear, 6 и 0
  - одредница: theory2, 0 и 2
  - одредница: theory2, 9 и 47
  - theory2 тѐо̄рија величѝна 10
  - theory0 тѐо̄рија величѝна 2
  - тѐо̄рија: theory0, square, 7 и 5
  - тѐо̄рија: theory3, linear, 5 и 2
  - theory1 тѐо̄рија величѝна 3
  - тѐо̄рија: theory2, сто̑л, 0 и 0
  - theory3 тѐо̄рија величѝна 3
  - одредница: theory2, 7 и 37
  - одредница: theory2, 12 и 62
  - одредница: theory2, 2 и 12
Податци:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Пра̏вило:
  - пра̏вило тѐо̄рија би̏ти lossless iff оно predvidjeti сва̏кӣ опа́жа̄ње тачно
  - пра̏вило изабрати lossless тѐо̄рија od minimalan величѝна
Сема̀нтика: linear oblik y = p1 * x + p2; square oblik y = x * x + p2; constant oblik y = p2; сто̑л oblik y = entry(x).
Smallest lossless тѐо̄рија kakav?

Ehdokkaat:
  - teoria: theory1, linear, 6 ja 0
  - artikkeli: theory2, 0 ja 2
  - artikkeli: theory2, 9 ja 47
  - theory2 teoria koko 10
  - theory0 teoria koko 2
  - teoria: theory0, square, 7 ja 5
  - teoria: theory3, linear, 5 ja 2
  - theory1 teoria koko 3
  - teoria: theory2, pöytä, 0 ja 0
  - theory3 teoria koko 3
  - artikkeli: theory2, 7 ja 37
  - artikkeli: theory2, 12 ja 62
  - artikkeli: theory2, 2 ja 12
Tieto:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Säännöt:
  - sääntö teoria tulla häviötön joss se ennakoida jokainen havainnointi täsmälleen
  - sääntö valita häviötön teoria vaille vähin koko
Semantiikka: linear muotoilla y = p1 * x + p2; square muotoilla y = x * x + p2; constant muotoilla y = p2; pöytä muotoilla y = entry(x).
Mikä smallest häviötön teoria?

候选项如下：
  - 的理论是：theory1、linear、6和0
  - 的条目是：theory2、0和2
  - 的条目是：theory2、9和47
  - theory2的理论规模是10
  - theory0的理论规模是2
  - 的理论是：theory0、square、7和5
  - 的理论是：theory3、linear、5和2
  - theory1的理论规模是3
  - 的理论是：theory2、桌子、0和0
  - theory3的理论规模是3
  - 的条目是：theory2、7和37
  - 的条目是：theory2、12和62
  - 的条目是：theory2、2和12
数据如下：
  - 2观察到12
  - 12观察到62
  - 7观察到37
  - 0观察到2
  - 9观察到47
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

候補者:
  - 理論:theory1, linear, 6と0
  - 項目:theory2, 0と2
  - 項目:theory2, 9と47
  - theory210理論大きさ
  - theory02理論大きさ
  - 理論:theory0, square, 7と5
  - 理論:theory3, linear, 5と2
  - theory13理論大きさ
  - 理論:theory2, 台, 0と0
  - theory33理論大きさ
  - 項目:theory2, 7と37
  - 項目:theory2, 12と62
  - 項目:theory2, 2と12
資料:
  - 212obs
  - 1262obs
  - 737obs
  - 02obs
  - 947obs
規則:規則:理論れるロスレスiffこれ予言する凡ゆる観察正確に; 規則:選ぶロスレス理論の中の最小の大きさ.
意味論:lineary = p1 * x + p2形作る; squarey = x * x + p2形作る; constanty = p2形作る; 台y = entry(x)形作る.
smallestロスレス理論何と?

Adaylar:
  - kuram: theory1, linear, 6 ve 0
  - entry: theory2, 0 ve 2
  - entry: theory2, 9 ve 47
  - theory2 10 kuram boyut
  - theory0 2 kuram boyut
  - kuram: theory0, square, 7 ve 5
  - kuram: theory3, linear, 5 ve 2
  - theory1 3 kuram boyut
  - kuram: theory2, masa, 0 ve 0
  - theory3 3 kuram boyut
  - entry: theory2, 7 ve 37
  - entry: theory2, 12 ve 62
  - entry: theory2, 2 ve 12
Veriler:
  - 2 12 obs
  - 12 62 obs
  - 7 37 obs
  - 0 2 obs
  - 9 47 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

مُرَشَّح:
  - نَظَرِيَّة: theory1، linear، 6 وَـ 0
  - مَدْخَل: theory2، 0 وَـ 2
  - مَدْخَل: theory2، 9 وَـ 47
  - نَظَرِيَّة مَقَاس theory2 10
  - نَظَرِيَّة مَقَاس theory0 2
  - نَظَرِيَّة: theory0، square، 7 وَـ 5
  - نَظَرِيَّة: theory3، linear، 5 وَـ 2
  - نَظَرِيَّة مَقَاس theory1 3
  - نَظَرِيَّة: theory2، طَاوِلَة، 0 وَـ 0
  - نَظَرِيَّة مَقَاس theory3 3
  - مَدْخَل: theory2، 7 وَـ 37
  - مَدْخَل: theory2، 12 وَـ 62
  - مَدْخَل: theory2، 2 وَـ 12
بَيَانَات:
  - obs 2 12
  - obs 12 62
  - obs 7 37
  - obs 0 2
  - obs 9 47
قَانُون:
  - قَانُون نَظَرِيَّة كَانَ lossless iff هُوَ تَنَبَّأَ كُلّ رَصْد بِالضَّبْط
  - قَانُون اِخْتَارَ الـ lossless نَظَرِيَّة مِنْ أَقَلَّ مَقَاس
عِلْم اَلْمَعَانِي: شَكَّلَ linear y = p1 * x + p2؛ شَكَّلَ square y = x * x + p2؛ شَكَّلَ constant y = p2؛ شَكَّلَ الـ طَاوِلَة y = entry(x).
smallest lossless نَظَرِيَّة مَاذَا؟

Კანდიდატები:
  - თეორია: theory1, linear, 6 და 0
  - სასათაურო სიტყვა: theory2, 0 და 2
  - სასათაურო სიტყვა: theory2, 9 და 47
  - theory2 10 თეორია ზომა
  - theory0 2 თეორია ზომა
  - თეორია: theory0, square, 7 და 5
  - თეორია: theory3, linear, 5 და 2
  - theory1 3 თეორია ზომა
  - თეორია: theory2, მაგიდა, 0 და 0
  - theory3 3 თეორია ზომა
  - სასათაურო სიტყვა: theory2, 7 და 37
  - სასათაურო სიტყვა: theory2, 12 და 62
  - სასათაურო სიტყვა: theory2, 2 და 12
Მონაცემები:
  - 2 12 obs
  - 12 62 obs
  - 7 37 obs
  - 0 2 obs
  - 9 47 obs
Წესი:
  - წესი თეორია ყოფნა უდანაკარგო iff ის predict ყველა დაკვირვება ზუსტად
  - წესი ამორჩევა უდანაკარგო თეორია of least ზომა
Სემანტიკა: linear y = p1 * x + p2 ბლანკი; square y = x * x + p2 ბლანკი; constant y = p2 ბლანკი; მაგიდა y = entry(x) ბლანკი.
Smallest უდანაკარგო თეორია რა?

Kaiwhakauru:
  - ariā: theory1, linear, 6 me 0
  - tāurunga: theory2, 0 me 2
  - tāurunga: theory2, 9 me 47
  - ariā size theory2 10
  - ariā size theory0 2
  - ariā: theory0, square, 7 me 5
  - ariā: theory3, linear, 5 me 2
  - ariā size theory1 3
  - ariā: theory2, tēpu, 0 me 0
  - ariā size theory3 3
  - tāurunga: theory2, 7 me 37
  - tāurunga: theory2, 12 me 62
  - tāurunga: theory2, 2 me 12
Hōtuku:
  - obs 2 12
  - obs 12 62
  - obs 7 37
  - obs 0 2
  - obs 9 47
Rekureihana:
  - rekureihana ariā is lossless iff it matakite every observation pū
  - rekureihana whiri te lossless ariā o least size
Semantics: āhua linear y = p1 * x + p2; āhua square y = x * x + p2; āhua constant y = p2; āhua te tēpu y = entry(x).
Smallest lossless ariā unutai?

Candidates:
  - lý thuyết: theory1, linear, 6 và 0
  - mục từ: theory2, 0 và 2
  - mục từ: theory2, 9 và 47
  - theory2 lý thuyết kích thước 10
  - theory0 lý thuyết kích thước 2
  - lý thuyết: theory0, square, 7 và 5
  - lý thuyết: theory3, linear, 5 và 2
  - theory1 lý thuyết kích thước 3
  - lý thuyết: theory2, bàn, 0 và 0
  - theory3 lý thuyết kích thước 3
  - mục từ: theory2, 7 và 37
  - mục từ: theory2, 12 và 62
  - mục từ: theory2, 2 và 12
Dữ liệu:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Quy tắc:
  - quy tắc lý thuyết được lossless iff nó dự báo mỗi observation đúng rồi
  - quy tắc chọn the lossless lý thuyết bằng least kích thước
Ngữ nghĩa: linear làm thành y = p1 * x + p2; square làm thành y = x * x + p2; constant làm thành y = p2; bàn làm thành y = entry(x).
Smallest lossless lý thuyết gì?

ผู้สมัคร:
  - ทฤษฎี:theory1, linear, 6และ0
  - entry:theory2, 0และ2
  - entry:theory2, 9และ47
  - theory2ทฤษฎีขนาด10
  - theory0ทฤษฎีขนาด2
  - ทฤษฎี:theory0, square, 7และ5
  - ทฤษฎี:theory3, linear, 5และ2
  - theory1ทฤษฎีขนาด3
  - ทฤษฎี:theory2, โต๊ะ, 0และ0
  - theory3ทฤษฎีขนาด3
  - entry:theory2, 7และ37
  - entry:theory2, 12และ62
  - entry:theory2, 2และ12
ข้อมูล:
  - 2obs12
  - 12obs62
  - 7obs37
  - 0obs2
  - 9obs47
กฎ:กฎ:ทฤษฎีถูกlosslessiffมันทำนายทุกการสังเกตexactly; กฎ:เลือกlosslessทฤษฎีของleastขนาด.
อรรถศาสตร์:linearรูปร่างy = p1 * x + p2; squareรูปร่างy = x * x + p2; constantรูปร่างy = p2; โต๊ะรูปร่างy = entry(x).
smallestlosslessทฤษฎีอะไร?

வேட்பாளர்:
  - theory: theory1, linear, 6 மற்றும் 0
  - உள்நுழைவதற்கு அனுமதி: theory2, 0 மற்றும் 2
  - உள்நுழைவதற்கு அனுமதி: theory2, 9 மற்றும் 47
  - theory2 10 theory size
  - theory0 2 theory size
  - theory: theory0, square, 7 மற்றும் 5
  - theory: theory3, linear, 5 மற்றும் 2
  - theory1 3 theory size
  - theory: theory2, மேசை, 0 மற்றும் 0
  - theory3 3 theory size
  - உள்நுழைவதற்கு அனுமதி: theory2, 7 மற்றும் 37
  - உள்நுழைவதற்கு அனுமதி: theory2, 12 மற்றும் 62
  - உள்நுழைவதற்கு அனுமதி: theory2, 2 மற்றும் 12
தரவுகள்:
  - 2 12 obs
  - 12 62 obs
  - 7 37 obs
  - 0 2 obs
  - 9 47 obs
rules: rule theory படு lossless iff it கணி ஒவ்வொரு observation exactly; rule choose lossless theory கொண்ட least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; மேசை y = entry(x) form.
smallest lossless theory என்ன?

Wagombea ni:
  - theory: theory1, linear, 6 na 0
  - entry: theory2, 0 na 2
  - entry: theory2, 9 na 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 na 5
  - theory: theory3, linear, 5 na 2
  - theory1 theory size 3
  - theory: theory2, meza, 0 na 0
  - theory3 theory size 3
  - entry: theory2, 7 na 37
  - entry: theory2, 12 na 62
  - entry: theory2, 2 na 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

Candidates:
  - theory: theory1, linear, 6 dóó 0
  - entry: theory2, 0 dóó 2
  - entry: theory2, 9 dóó 47
  - theory2 10 theory size
  - theory0 2 theory size
  - theory: theory0, square, 7 dóó 5
  - theory: theory3, linear, 5 dóó 2
  - theory1 3 theory size
  - theory: theory2, bikááʼ adání, 0 dóó 0
  - theory3 3 theory size
  - entry: theory2, 7 dóó 37
  - entry: theory2, 12 dóó 62
  - entry: theory2, 2 dóó 12
Data:
  - 2 12 obs
  - 12 62 obs
  - 7 37 obs
  - 0 2 obs
  - 9 47 obs
Bee hazʼáanii:
  - bee hazʼáanii theory átʼé lossless iff it predict every observation exactly
  - bee hazʼáanii choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; bikááʼ adání y = entry(x) form.
Smallest lossless theory haʼátʼíísh?

Candidates:
  - theory: theory1, linear, 6 aamma 0
  - entry: theory2, 0 aamma 2
  - entry: theory2, 9 aamma 47
  - theory2 10 theory size
  - theory0 2 theory size
  - theory: theory0, square, 7 aamma 5
  - theory: theory3, linear, 5 aamma 2
  - theory1 3 theory size
  - theory: theory2, table, 0 aamma 0
  - theory3 3 theory size
  - entry: theory2, 7 aamma 37
  - entry: theory2, 12 aamma 62
  - entry: theory2, 2 aamma 12
Data:
  - 2 12 obs
  - 12 62 obs
  - 7 37 obs
  - 0 2 obs
  - 9 47 obs
Rules: rule theory a lossless iff una predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 blanketti; square y = x * x + p2 blanketti; constant y = p2 blanketti; table y = entry(x) blanketti.
Smallest lossless theory what?

Candidates:
  - theory: theory1, linear, 6 na 0
  - entry: theory2, 0 na 2
  - entry: theory2, 9 na 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 na 5
  - theory: theory3, linear, 5 na 2
  - theory1 theory size 3
  - theory: theory2, table, 0 na 0
  - theory3 theory size 3
  - entry: theory2, 7 na 37
  - entry: theory2, 12 na 62
  - entry: theory2, 2 na 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory bilong least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, linear, 6 0
  - entry: theory2, 0 2
  - entry: theory2, 9 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 5
  - theory: theory3, linear, 5 2
  - theory1 theory size 3
  - theory: theory2, table, 0 0
  - theory3 theory size 3
  - entry: theory2, 7 37
  - entry: theory2, 12 62
  - entry: theory2, 2 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Nikanixi:
  - nikanixi theory is lossless iff it predict every observation exactly
  - nikanixi choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory kwèch?

Candidates:
  - theory: theory1, linear, 6 а 0
  - entry: theory2, 0 а 2
  - entry: theory2, 9 а 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 а 5
  - theory: theory3, linear, 5 а 2
  - theory1 theory size 3
  - theory: theory2, table, 0 а 0
  - theory3 theory size 3
  - entry: theory2, 7 а 37
  - entry: theory2, 12 а 62
  - entry: theory2, 2 а 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Rules:
  - rule theory хила lossless iff it predict дерриг observation exactly
  - rule хержа lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory фу?

후보자:
  - 이론: theory1, linear, 6 0
  - 항목: theory2, 0 2
  - 항목: theory2, 9 47
  - theory2 10 이론 크기
  - theory0 2 이론 크기
  - 이론: theory0, square, 7 5
  - 이론: theory3, linear, 5 2
  - theory1 3 이론 크기
  - 이론: theory2, 테이블, 0 0
  - theory3 3 이론 크기
  - 항목: theory2, 7 37
  - 항목: theory2, 12 62
  - 항목: theory2, 2 12
자료:
  - 2 12 obs
  - 12 62 obs
  - 7 37 obs
  - 0 2 obs
  - 9 47 obs
규칙: 규칙 이론 is lossless iff 이것 예언하다 각 관찰 정확하게; 규칙 고르다 lossless 이론...의 가장 적게 크기.
의미론: linear y = p1 * x + p2 형상; square y = x * x + p2 형상; constant y = p2 형상; 테이블 y = entry(x) 형상.
smallest lossless 이론 무엇?

Kandidatu:
  - theory: theory1, linear, 6 eta 0
  - sarrera: theory2, 0 eta 2
  - sarrera: theory2, 9 eta 47
  - theory2 10 theory tamaina
  - theory0 2 theory tamaina
  - theory: theory0, square, 7 eta 5
  - theory: theory3, linear, 5 eta 2
  - theory1 3 theory tamaina
  - theory: theory2, mahai, 0 eta 0
  - theory3 3 theory tamaina
  - sarrera: theory2, 7 eta 37
  - sarrera: theory2, 12 eta 62
  - sarrera: theory2, 2 eta 12
Data:
  - 2 12 obs
  - 12 62 obs
  - 7 37 obs
  - 0 2 obs
  - 9 47 obs
Arau:
  - arau bat theory izan lossless iff it aurresan every observation exactly
  - arau aukeratu the lossless theory of least tamaina
Semantics: linear y = p1 * x + p2 forma; square y = x * x + p2 forma; constant y = p2 forma; mahai y = entry(x) forma.
Smallest lossless theory zer?

ᎠᏙᎩᏯᏍᎩ:
  - theory: theory1, linear, 6 ᎠᎴ 0
  - entry: theory2, 0 ᎠᎴ 2
  - entry: theory2, 9 ᎠᎴ 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 ᎠᎴ 5
  - theory: theory3, linear, 5 ᎠᎴ 2
  - theory1 theory size 3
  - theory: theory2, ᎦᏍᎩᎶ, 0 ᎠᎴ 0
  - theory3 theory size 3
  - entry: theory2, 7 ᎠᎴ 37
  - entry: theory2, 12 ᎠᎴ 62
  - entry: theory2, 2 ᎠᎴ 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ᎦᏍᎩᎶ form y = entry(x).
What smallest lossless theory?

Candidates:
  - theory: theory1, linear, 6 0
  - entry: theory2, 0 2
  - entry: theory2, 9 47
  - theory2 theory chhika 10
  - theory0 theory chhika 2
  - theory: theory0, square, 7 5
  - theory: theory3, linear, 5 2
  - theory1 theory chhika 3
  - theory: theory2, patacha, 0 0
  - theory3 theory chhika 3
  - entry: theory2, 7 37
  - entry: theory2, 12 62
  - entry: theory2, 2 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Rules:
  - rule theory tiyay lossless iff it predict tukuy observation exactly
  - rule akllay lossless theory of least chhika
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; patacha form y = entry(x).
Smallest lossless theory what?

Candidates:
  - тиориэ: theory1, linear, 6 ыкӏи 0
  - entry: theory2, 0 ыкӏи 2
  - entry: theory2, 9 ыкӏи 47
  - theory2 10 тиориэ size
  - theory0 2 тиориэ size
  - тиориэ: theory0, square, 7 ыкӏи 5
  - тиориэ: theory3, linear, 5 ыкӏи 2
  - theory1 3 тиориэ size
  - тиориэ: theory2, table, 0 ыкӏи 0
  - theory3 3 тиориэ size
  - entry: theory2, 7 ыкӏи 37
  - entry: theory2, 12 ыкӏи 62
  - entry: theory2, 2 ыкӏи 12
Data:
  - 2 12 obs
  - 12 62 obs
  - 7 37 obs
  - 0 2 obs
  - 9 47 obs
Rules: rule тиориэ is lossless iff it predict every observation exactly; rule choose the lossless тиориэ of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless тиориэ сыд?

Candidates:
  - theory: theory1, linear, 6 thiab 0
  - entry: theory2, 0 thiab 2
  - entry: theory2, 9 thiab 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 thiab 5
  - theory: theory3, linear, 5 thiab 2
  - theory1 theory size 3
  - theory: theory2, rooj, 0 thiab 0
  - theory3 theory size 3
  - entry: theory2, 7 thiab 37
  - entry: theory2, 12 thiab 62
  - entry: theory2, 2 thiab 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Cai: cai theory is lossless iff nws predict every observation exactly; cai choose lossless theory of least size.
Lub ntsiab: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; rooj form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, linear, 6 0
  - entry: theory2, 0 2
  - entry: theory2, 9 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 5
  - theory: theory3, linear, 5 2
  - theory1 theory size 3
  - theory: theory2, table, 0 0
  - theory3 theory size 3
  - entry: theory2, 7 37
  - entry: theory2, 12 62
  - entry: theory2, 2 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of wy krook size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory ining-jak?

Candidates:
  - theory: theory1, linear, 6 micha' 0
  - entry: theory2, 0 micha' 2
  - entry: theory2, 9 micha' 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 micha' 5
  - theory: theory3, linear, 5 micha' 2
  - theory1 theory size 3
  - theory: theory2, table, 0 micha' 0
  - theory3 theory size 3
  - entry: theory2, 7 micha' 37
  - entry: theory2, 12 micha' 62
  - entry: theory2, 2 micha' 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory nanta?

Candidates:
  - theory: theory1, linear, 6 カ 0
  - entry: theory2, 0 カ 2
  - entry: theory2, 9 カ 47
  - theory2 10 theory size
  - theory0 2 theory size
  - theory: theory0, square, 7 カ 5
  - theory: theory3, linear, 5 カ 2
  - theory1 3 theory size
  - theory: theory2, table, 0 カ 0
  - theory3 3 theory size
  - entry: theory2, 7 カ 37
  - entry: theory2, 12 カ 62
  - entry: theory2, 2 カ 12
Data:
  - 2 12 obs
  - 12 62 obs
  - 7 37 obs
  - 0 2 obs
  - 9 47 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 ノカ; square y = x * x + p2 ノカ; constant y = p2 ノカ; table y = entry(x) ノカ.
Smallest lossless theory what?

Candidates:
  - theory: theory1, linear, 6 ынкъам 0
  - entry: theory2, 0 ынкъам 2
  - entry: theory2, 9 ынкъам 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 ынкъам 5
  - theory: theory3, linear, 5 ынкъам 2
  - theory1 theory size 3
  - theory: theory2, table, 0 ынкъам 0
  - theory3 theory size 3
  - entry: theory2, 7 ынкъам 37
  - entry: theory2, 12 ынкъам 62
  - entry: theory2, 2 ынкъам 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, linear, 6 yéetel 0
  - entry: theory2, 0 yéetel 2
  - entry: theory2, 9 yéetel 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 yéetel 5
  - theory: theory3, linear, 5 yéetel 2
  - theory1 theory size 3
  - theory: theory2, table, 0 yéetel 0
  - theory3 theory size 3
  - entry: theory2, 7 yéetel 37
  - entry: theory2, 12 yéetel 62
  - entry: theory2, 2 yéetel 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Rules:
  - rule theory yan lossless iff it predict every observation exactly
  - rule yéey lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, linear, 6 0
  - entry: theory2, 0 2
  - entry: theory2, 9 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 5
  - theory: theory3, linear, 5 2
  - theory1 theory size 3
  - theory: theory2, mę́soną, 0 0
  - theory3 theory size 3
  - entry: theory2, 7 37
  - entry: theory2, 12 62
  - entry: theory2, 2 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Rules:
  - rule theory is lossless iff ą́wąną predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mę́soną form y = entry(x).
Smallest lossless theory híli?

Candidates:
  - theory: theory1, linear, 6 na 0
  - entry: theory2, 0 na 2
  - entry: theory2, 9 na 47
  - theory2 10 theory size
  - theory0 2 theory size
  - theory: theory0, square, 7 na 5
  - theory: theory3, linear, 5 na 2
  - theory1 3 theory size
  - theory: theory2, table, 0 na 0
  - theory3 3 theory size
  - entry: theory2, 7 na 37
  - entry: theory2, 12 na 62
  - entry: theory2, 2 na 12
Data:
  - 2 12 obs
  - 12 62 obs
  - 7 37 obs
  - 0 2 obs
  - 9 47 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory1, linear, 6 0
  - entry: theory2, 0 2
  - entry: theory2, 9 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 5
  - theory: theory3, linear, 5 2
  - theory1 theory size 3
  - theory: theory2, table, 0 0
  - theory3 theory size 3
  - entry: theory2, 7 37
  - entry: theory2, 12 62
  - entry: theory2, 2 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, linear, 6 0
  - entry: theory2, 0 2
  - entry: theory2, 9 47
  - theory2 10 theory size
  - theory0 2 theory size
  - theory: theory0, square, 7 5
  - theory: theory3, linear, 5 2
  - theory1 3 theory size
  - theory: theory2, table, 0 0
  - theory3 3 theory size
  - entry: theory2, 7 37
  - entry: theory2, 12 62
  - entry: theory2, 2 12
Data:
  - 2 12 obs
  - 12 62 obs
  - 7 37 obs
  - 0 2 obs
  - 9 47 obs
Rules:
  - rule maya theory is lossless iff it predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory1, linear, 6 ǂʻá 0
  - entry: theory2, 0 ǂʻá 2
  - entry: theory2, 9 ǂʻá 47
  - theory2 theory ʻǁnàhã 10
  - theory0 theory ʻǁnàhã 2
  - theory: theory0, square, 7 ǂʻá 5
  - theory: theory3, linear, 5 ǂʻá 2
  - theory1 theory ʻǁnàhã 3
  - theory: theory2, table, 0 ǂʻá 0
  - theory3 theory ʻǁnàhã 3
  - entry: theory2, 7 ǂʻá 37
  - entry: theory2, 12 ǂʻá 62
  - entry: theory2, 2 ǂʻá 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Rules:
  - rule theory ǀîi lossless iff èh predict every observation exactly
  - rule choose lossless theory of least ʻǁnàhã
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, linear, 6 0
  - entry: theory2, 0 2
  - entry: theory2, 9 47
  - theory2 10 theory size
  - theory0 2 theory size
  - theory: theory0, square, 7 5
  - theory: theory3, linear, 5 2
  - theory1 3 theory size
  - theory: theory2, остол, 0 0
  - theory3 3 theory size
  - entry: theory2, 7 37
  - entry: theory2, 12 62
  - entry: theory2, 2 12
Data:
  - 2 12 obs
  - 12 62 obs
  - 7 37 obs
  - 0 2 obs
  - 9 47 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; остол y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory1, linear, 6 0
  - entry: theory2, 0 2
  - entry: theory2, 9 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 5
  - theory: theory3, linear, 5 2
  - theory1 theory size 3
  - theory: theory2, table, 0 0
  - theory3 theory size 3
  - entry: theory2, 7 37
  - entry: theory2, 12 62
  - entry: theory2, 2 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, linear, 6 0
  - entry: theory2, 0 2
  - entry: theory2, 9 47
  - theory2 10 theory size
  - theory0 2 theory size
  - theory: theory0, square, 7 5
  - theory: theory3, linear, 5 2
  - theory1 3 theory size
  - theory: theory2, table, 0 0
  - theory3 3 theory size
  - entry: theory2, 7 37
  - entry: theory2, 12 62
  - entry: theory2, 2 12
Data:
  - 2 12 obs
  - 12 62 obs
  - 7 37 obs
  - 0 2 obs
  - 9 47 obs
Rules:
  - rule theory is lossless iff kitu predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory1, linear, 6 0
  - entry: theory2, 0 2
  - entry: theory2, 9 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 5
  - theory: theory3, linear, 5 2
  - theory1 theory size 3
  - theory: theory2, mesa, 0 0
  - theory3 theory size 3
  - entry: theory2, 7 37
  - entry: theory2, 12 62
  - entry: theory2, 2 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mesa form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, linear, 6 0
  - entry: theory2, 0 2
  - entry: theory2, 9 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 5
  - theory: theory3, linear, 5 2
  - theory1 theory size 3
  - theory: theory2, table, 0 0
  - theory3 theory size 3
  - entry: theory2, 7 37
  - entry: theory2, 12 62
  - entry: theory2, 2 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Rules:
  - rule theory nemi lossless iff yaja predict every observation exactly
  - rule choose ne lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ne table form y = entry(x).
Smallest lossless theory tay?

Les candidats sont:
  - théorie: theory1, linear, 6 et 0
  - article: theory2, 0 et 2
  - article: theory2, 9 et 47
  - theory2 théorie taille 10
  - theory0 théorie taille 2
  - théorie: theory0, square, 7 et 5
  - théorie: theory3, linear, 5 et 2
  - theory1 théorie taille 3
  - théorie: theory2, table, 0 et 0
  - theory3 théorie taille 3
  - article: theory2, 7 et 37
  - article: theory2, 12 et 62
  - article: theory2, 2 et 12
Les données sont:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Les règles sont:
  - règle un théorie être lossless ssi il prédire tout observation exactement
  - règle choisir le lossless théorie du moindre taille
La sémantique est : linear former y = p1 * x + p2 ; square former y = x * x + p2 ; constant former y = p2 ; la table former y = entry(x).
Quoi smallest lossless théorie ?

Kandidato:
  - teorio: theory1, linear, 6 kaj 0
  - entry: theory2, 0 kaj 2
  - entry: theory2, 9 kaj 47
  - theory2 teorio grandeco 10
  - theory0 teorio grandeco 2
  - teorio: theory0, square, 7 kaj 5
  - teorio: theory3, linear, 5 kaj 2
  - theory1 teorio grandeco 3
  - teorio: theory2, tablo, 0 kaj 0
  - theory3 teorio grandeco 3
  - entry: theory2, 7 kaj 37
  - entry: theory2, 12 kaj 62
  - entry: theory2, 2 kaj 12
Datumo:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Regulo: regulo teorio egali lossless iff ĝi predict ĉiu observo ekzakte; regulo elekti lossless teorio de plej malmulta grandeco.
Semantics: linear formi y = p1 * x + p2; square formi y = x * x + p2; constant formi y = p2; tablo formi y = entry(x).
Smallest lossless teorio kio?

Indulók:
  - elmélet: theory1, linear, 6 és 0
  - szócikk: theory2, 0 és 2
  - szócikk: theory2, 9 és 47
  - theory2 elmélet méret 10
  - theory0 elmélet méret 2
  - elmélet: theory0, square, 7 és 5
  - elmélet: theory3, linear, 5 és 2
  - theory1 elmélet méret 3
  - elmélet: theory2, asztal, 0 és 0
  - theory3 elmélet méret 3
  - szócikk: theory2, 7 és 37
  - szócikk: theory2, 12 és 62
  - szócikk: theory2, 2 és 12
Adat:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Szabályok:
  - szabály elmélet van veszteségmentes acsa az megjósol minden megfigyelés pontosan
  - szabály kiválaszt a veszteségmentes elmélet of legkisebb méret
Szemantika: linear kialakít y = p1 * x + p2; square kialakít y = x * x + p2; constant kialakít y = p2; a asztal kialakít y = entry(x).
Smallest veszteségmentes elmélet melyik?

候選人:
  - theory:theory1, linear, 6及0
  - entry:theory2, 0及2
  - entry:theory2, 9及47
  - theory2theory size10
  - theory0theory size2
  - theory:theory0, square, 7及5
  - theory:theory3, linear, 5及2
  - theory1theory size3
  - theory:theory2, 檯, 0及0
  - theory3theory size3
  - entry:theory2, 7及37
  - entry:theory2, 12及62
  - entry:theory2, 2及12
數據:
  - 2obs12
  - 12obs62
  - 7obs37
  - 0obs2
  - 9obs47
rules:rule:一theory是losslessiffitpredict每observationexactly; rule:揀losslesstheory...嘅leastsize.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; 檯formy = entry(x).
smallest lossless theory乜嘢?

Candidates:
  - theory: theory1, linear, 6 とぅ 0
  - entry: theory2, 0 とぅ 2
  - entry: theory2, 9 とぅ 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 とぅ 5
  - theory: theory3, linear, 5 とぅ 2
  - theory1 theory size 3
  - theory: theory2, table, 0 とぅ 0
  - theory3 theory size 3
  - entry: theory2, 7 とぅ 37
  - entry: theory2, 12 とぅ 62
  - entry: theory2, 2 とぅ 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Rules: rule theory 有ん lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Үміткер:
  - теория: theory1, linear, 6 және 0
  - entry: theory2, 0 және 2
  - entry: theory2, 9 және 47
  - theory2 теория мөлшер 10
  - theory0 теория мөлшер 2
  - теория: theory0, square, 7 және 5
  - теория: theory3, linear, 5 және 2
  - theory1 теория мөлшер 3
  - теория: theory2, үстел, 0 және 0
  - theory3 теория мөлшер 3
  - entry: theory2, 7 және 37
  - entry: theory2, 12 және 62
  - entry: theory2, 2 және 12
Деректер:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Ереже: ереже теория is lossless iff ол predict әр бақылау exactly; ереже таңдау lossless теория туралы least мөлшер.
Семантикалық: linear пішін y = p1 * x + p2; square пішін y = x * x + p2; constant пішін y = p2; үстел пішін y = entry(x).
Smallest lossless теория не?

מועמדת:
  - תּוֹרָה: theory1, linear, 6 וְ־ 0
  - entry: theory2, 0 וְ־ 2
  - entry: theory2, 9 וְ־ 47
  - theory2 תּוֹרָה גֹּדֶל 10
  - theory0 תּוֹרָה גֹּדֶל 2
  - תּוֹרָה: theory0, square, 7 וְ־ 5
  - תּוֹרָה: theory3, linear, 5 וְ־ 2
  - theory1 תּוֹרָה גֹּדֶל 3
  - תּוֹרָה: theory2, טַבְלָה, 0 וְ־ 0
  - theory3 תּוֹרָה גֹּדֶל 3
  - entry: theory2, 7 וְ־ 37
  - entry: theory2, 12 וְ־ 62
  - entry: theory2, 2 וְ־ 12
נְתוּנִים:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
מָשַׁל:
  - מָשַׁל אַחַת תּוֹרָה הוא lossless אםם זֶה predict כֹּל תַּצְפִּית בדיוק
  - מָשַׁל בחר ה־ lossless תּוֹרָה שֶׁל least גֹּדֶל
תורת המשמעים: linear צורה y = p1 * x + p2; square צורה y = x * x + p2; constant צורה y = p2; טַבְלָה ה־ צורה y = entry(x).
איזה smallest lossless תּוֹרָה?

Candidates:
  - theory: theory1, linear, 6 დო 0
  - entry: theory2, 0 დო 2
  - entry: theory2, 9 დო 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 დო 5
  - theory: theory3, linear, 5 დო 2
  - theory1 theory size 3
  - theory: theory2, table, 0 დო 0
  - theory3 theory size 3
  - entry: theory2, 7 დო 37
  - entry: theory2, 12 დო 62
  - entry: theory2, 2 დო 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Kandidat:
  - teori: theory1, linear, 6 dan 0
  - lema: theory2, 0 dan 2
  - lema: theory2, 9 dan 47
  - theory2 teori ukuran 10
  - theory0 teori ukuran 2
  - teori: theory0, square, 7 dan 5
  - teori: theory3, linear, 5 dan 2
  - theory1 teori ukuran 3
  - teori: theory2, meja, 0 dan 0
  - theory3 teori ukuran 3
  - lema: theory2, 7 dan 37
  - lema: theory2, 12 dan 62
  - lema: theory2, 2 dan 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Rules:
  - rule teori berada lossless iff it predict setiap observation tepat
  - rule memilih si lossless teori dari least ukuran
Semantik: linear formulir y = p1 * x + p2; square formulir y = x * x + p2; constant formulir y = p2; meja si formulir y = entry(x).
Smallest lossless teori apa?

បេក្ខជន:
  - ទ្រឹស្ដី:theory1, linear, 6នឹង0
  - មេពាក្យ:theory2, 0នឹង2
  - មេពាក្យ:theory2, 9នឹង47
  - theory2ទ្រឹស្ដីទំហំ10
  - theory0ទ្រឹស្ដីទំហំ2
  - ទ្រឹស្ដី:theory0, square, 7នឹង5
  - ទ្រឹស្ដី:theory3, linear, 5នឹង2
  - theory1ទ្រឹស្ដីទំហំ3
  - ទ្រឹស្ដី:theory2, តុ, 0នឹង0
  - theory3ទ្រឹស្ដីទំហំ3
  - មេពាក្យ:theory2, 7នឹង37
  - មេពាក្យ:theory2, 12នឹង62
  - មេពាក្យ:theory2, 2នឹង12
ទិន្នន័យ:
  - 2obs12
  - 12obs62
  - 7obs37
  - 0obs2
  - 9obs47
ក្បួន:ក្បួន:ទ្រឹស្ដីត្រូវបានlosslessiffវាចាប់យាមរាល់គំនន់exactly; ក្បួន:រើសthelosslessទ្រឹស្ដីនៃleastទំហំ.
និឃណ្ដសាស្ត្រ:linearគ្រោងy = p1 * x + p2; squareគ្រោងy = x * x + p2; constantគ្រោងy = p2; តុគ្រោងy = entry(x).
smallestlosslessទ្រឹស្ដីអី?

ຜູ້ສະໝັກ:
  - ທິດສະດີ:theory1, linear, 6ແລະ0
  - entry:theory2, 0ແລະ2
  - entry:theory2, 9ແລະ47
  - theory2ທິດສະດີຂະຫນາດ10
  - theory0ທິດສະດີຂະຫນາດ2
  - ທິດສະດີ:theory0, square, 7ແລະ5
  - ທິດສະດີ:theory3, linear, 5ແລະ2
  - theory1ທິດສະດີຂະຫນາດ3
  - ທິດສະດີ:theory2, ໂຕະ, 0ແລະ0
  - theory3ທິດສະດີຂະຫນາດ3
  - entry:theory2, 7ແລະ37
  - entry:theory2, 12ແລະ62
  - entry:theory2, 2ແລະ12
ຂໍ້ມູນ:
  - 2obs12
  - 12obs62
  - 7obs37
  - 0obs2
  - 9obs47
ກະຕິກາ:ກະຕິກາ:ທິດສະດີຢູ່losslessiffມັນທຳນວາຍທຸກobservationexactly; ກະຕິກາ:ເລືອກlosslessທິດສະດີຂອງleastຂະຫນາດ.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; ໂຕະformy = entry(x).
smallestlosslessທິດສະດີຫຍັງ?

candidates:
  - theory: theory1, linear, 6 మరియు 0
  - entry: theory2, 0 మరియు 2
  - entry: theory2, 9 మరియు 47
  - theory2 10 theory size
  - theory0 2 theory size
  - theory: theory0, square, 7 మరియు 5
  - theory: theory3, linear, 5 మరియు 2
  - theory1 3 theory size
  - theory: theory2, బల్ల, 0 మరియు 0
  - theory3 3 theory size
  - entry: theory2, 7 మరియు 37
  - entry: theory2, 12 మరియు 62
  - entry: theory2, 2 మరియు 12
data:
  - 2 12 obs
  - 12 62 obs
  - 7 37 obs
  - 0 2 obs
  - 9 47 obs
నియమం: నియమం theory ఉండు lossless iff it predict ప్రతి పరిశీలన exactly; నియమం choose lossless theory of least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; బల్ల y = entry(x) form.
smallest lossless theory ఏమిటి?

Candidates:
  - theory: theory1, linear, 6 0
  - entry: theory2, 0 2
  - entry: theory2, 9 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 5
  - theory: theory3, linear, 5 2
  - theory1 theory size 3
  - theory: theory2, table, 0 0
  - theory3 theory size 3
  - entry: theory2, 7 37
  - entry: theory2, 12 62
  - entry: theory2, 2 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Rules: rule theory wà lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
What smallest lossless theory?

Candidates:
  - theory: theory1, linear, 6 0
  - entry: theory2, 0 2
  - entry: theory2, 9 47
  - theory2 10 theory size
  - theory0 2 theory size
  - theory: theory0, square, 7 5
  - theory: theory3, linear, 5 2
  - theory1 3 theory size
  - theory: theory2, table, 0 0
  - theory3 3 theory size
  - entry: theory2, 7 37
  - entry: theory2, 12 62
  - entry: theory2, 2 12
Data:
  - 2 12 obs
  - 12 62 obs
  - 7 37 obs
  - 0 2 obs
  - 9 47 obs
Rules:
  - rule theory naiágúóli lossless iff it predict every observation exactly
  - rule choose the lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

candidates:
  - theory: theory1, linear, 6 0
  - entry: theory2, 0 2
  - entry: theory2, 9 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 5
  - theory: theory3, linear, 5 2
  - theory1 theory size 3
  - theory: theory2, table, 0 0
  - theory3 theory size 3
  - entry: theory2, 7 37
  - entry: theory2, 12 62
  - entry: theory2, 2 12
data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
smallest lossless theory what?

Candidates:
  - theory: theory1, linear, 6 0
  - entry: theory2, 0 2
  - entry: theory2, 9 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 5
  - theory: theory3, linear, 5 2
  - theory1 theory size 3
  - theory: theory2, tafra, 0 0
  - theory3 theory size 3
  - entry: theory2, 7 37
  - entry: theory2, 12 62
  - entry: theory2, 2 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; tafra form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, linear, 6 0
  - entry: theory2, 0 2
  - entry: theory2, 9 47
  - theory2 theory size 10
  - theory0 theory size 2
  - theory: theory0, square, 7 5
  - theory: theory3, linear, 5 2
  - theory1 theory size 3
  - theory: theory2, táxemésėhestȯtse, 0 0
  - theory3 theory size 3
  - entry: theory2, 7 37
  - entry: theory2, 12 62
  - entry: theory2, 2 12
Data:
  - 2 obs 12
  - 12 obs 62
  - 7 obs 37
  - 0 obs 2
  - 9 obs 47
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; táxemésėhestȯtse form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, linear, 6 0
  - entry: theory2, 0 2
  - entry: theory2, 9 47
  - theory2 10 theory size
  - theory0 2 theory size
  - theory: theory0, square, 7 5
  - theory: theory3, linear, 5 2
  - theory1 3 theory size
  - theory: theory2, ствал, 0 0
  - theory3 3 theory size
  - entry: theory2, 7 37
  - entry: theory2, 12 62
  - entry: theory2, 2 12
Data:
  - 2 12 obs
  - 12 62 obs
  - 7 37 obs
  - 0 2 obs
  - 9 47 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; ствал y = entry(x) form.
Smallest lossless theory вуч?

The candidates are:
  - theory: theory1, square, 2 and 4
  - theory: theory2, linear, 4 and -5
  - entry: theory0, 8 and 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 and 7
  - entry: theory0, 10 and 106
  - theory: theory0, table, 0 and 0
  - entry: theory0, 12 and 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 and 6
  - theory: theory3, square, 3 and 6
The data are:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

Los candidatos son:
  - la teoría: theory1, square, 2 y 4
  - la teoría: theory2, linear, 4 y -5
  - la entrada: theory0, 8 y 70
  - theory1 el tamaño de la teoría 2
  - theory0 el tamaño de la teoría 10
  - la entrada: theory0, 1 y 7
  - la entrada: theory0, 10 y 106
  - la teoría: theory0, mesa, 0 y 0
  - la entrada: theory0, 12 y 150
  - theory2 el tamaño de la teoría 3
  - theory3 el tamaño de la teoría 2
  - la entrada: theory0, 0 y 6
  - la teoría: theory3, square, 3 y 6
Los datos son:
  - 1 la observación 7
  - 8 la observación 70
  - 12 la observación 150
  - 0 la observación 6
  - 10 la observación 106
Las reglas son:
  - la regla: a la teoría es lossless si y sólo si it predice every observation exactamente
  - la regla: choose el lossless la teoría de least tamaño
La semántica es: linear la forma y = p1 * x + p2; square la forma y = x * x + p2; constant la forma y = p2; la mesa la forma y = entry(x).
¿Qué smallest lossless la teoría?

候选项如下：
  - 的理论是：theory1、square、2和4
  - 的理论是：theory2、linear、4和-5
  - 的条目是：theory0、8和70
  - theory1的理论规模是2
  - theory0的理论规模是10
  - 的条目是：theory0、1和7
  - 的条目是：theory0、10和106
  - 的理论是：theory0、桌子、0和0
  - 的条目是：theory0、12和150
  - theory2的理论规模是3
  - theory3的理论规模是2
  - 的条目是：theory0、0和6
  - 的理论是：theory3、square、3和6
数据如下：
  - 1观察到7
  - 8观察到70
  - 12观察到150
  - 0观察到6
  - 10观察到106
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

Adaylar:
  - kuram: theory1, square, 2 ve 4
  - kuram: theory2, linear, 4 ve -5
  - entry: theory0, 8 ve 70
  - theory1 2 kuram boyut
  - theory0 10 kuram boyut
  - entry: theory0, 1 ve 7
  - entry: theory0, 10 ve 106
  - kuram: theory0, masa, 0 ve 0
  - entry: theory0, 12 ve 150
  - theory2 3 kuram boyut
  - theory3 2 kuram boyut
  - entry: theory0, 0 ve 6
  - kuram: theory3, square, 3 ve 6
Veriler:
  - 1 7 obs
  - 8 70 obs
  - 12 150 obs
  - 0 6 obs
  - 10 106 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

Wagombea ni:
  - theory: theory1, square, 2 na 4
  - theory: theory2, linear, 4 na -5
  - entry: theory0, 8 na 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 na 7
  - entry: theory0, 10 na 106
  - theory: theory0, meza, 0 na 0
  - entry: theory0, 12 na 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 na 6
  - theory: theory3, square, 3 na 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

The candidates are:
  - theory: theory1, square, 2 and 4
  - theory: theory2, linear, 4 and -5
  - entry: theory0, 8 and 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 and 7
  - entry: theory0, 10 and 106
  - theory: theory0, table, 0 and 0
  - entry: theory0, 12 and 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 and 6
  - theory: theory3, square, 3 and 6
The data are:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

{candidates: [(theory theory1 square 2 4) (theory theory2 linear 4 -5) (entry theory0 8 70) (theory_size theory1 2) (theory_size theory0 10) (entry theory0 1 7) (entry theory0 10 106) (theory theory0 table 0 0) (entry theory0 12 150) (theory_size theory2 3) (theory_size theory3 2) (entry theory0 0 6) (theory theory3 square 3 6)], data: [(obs 1 7) (obs 8 70) (obs 12 150) (obs 0 6) (obs 10 106)], query: smallest_lossless_theory, rules: [(rule (a_theory_is_lossless_iff_it_predicts_every_observation_exactly)) (rule (choose_the_lossless_theory_of_least_size))], semantics: [(form linear "y = p1 * x + p2") (form square "y = x * x + p2") (form constant "y = p2") (form table "y = entry(x)")]}

Die Kandidaten sind:
  - Theorie: theory1, square, 2 und 4
  - Theorie: theory2, linear, 4 und -5
  - Eintrag: theory0, 8 und 70
  - theory1 Theorie Größe 2
  - theory0 Theorie Größe 10
  - Eintrag: theory0, 1 und 7
  - Eintrag: theory0, 10 und 106
  - Theorie: theory0, Tisch, 0 und 0
  - Eintrag: theory0, 12 und 150
  - theory2 Theorie Größe 3
  - theory3 Theorie Größe 2
  - Eintrag: theory0, 0 und 6
  - Theorie: theory3, square, 3 und 6
Die Daten sind:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Die Regeln sind:
  - Regel ein Theorie werden verlustfrei gdw. er vorhersagen jeder Beobachtung genau
  - Regel wählen der verlustfrei Theorie aus geringst Größe
Die Semantik ist: linear formen y = p1 * x + p2; square formen y = x * x + p2; constant formen y = p2; der Tisch formen y = entry(x).
Was smallest verlustfrei Theorie?

Кандѝда̄т:
  - тѐо̄рија: theory1, square, 2 и 4
  - тѐо̄рија: theory2, linear, 4 и -5
  - одредница: theory0, 8 и 70
  - theory1 тѐо̄рија величѝна 2
  - theory0 тѐо̄рија величѝна 10
  - одредница: theory0, 1 и 7
  - одредница: theory0, 10 и 106
  - тѐо̄рија: theory0, сто̑л, 0 и 0
  - одредница: theory0, 12 и 150
  - theory2 тѐо̄рија величѝна 3
  - theory3 тѐо̄рија величѝна 2
  - одредница: theory0, 0 и 6
  - тѐо̄рија: theory3, square, 3 и 6
Податци:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Пра̏вило:
  - пра̏вило тѐо̄рија би̏ти lossless iff оно predvidjeti сва̏кӣ опа́жа̄ње тачно
  - пра̏вило изабрати lossless тѐо̄рија od minimalan величѝна
Сема̀нтика: linear oblik y = p1 * x + p2; square oblik y = x * x + p2; constant oblik y = p2; сто̑л oblik y = entry(x).
Smallest lossless тѐо̄рија kakav?

Ehdokkaat:
  - teoria: theory1, square, 2 ja 4
  - teoria: theory2, linear, 4 ja -5
  - artikkeli: theory0, 8 ja 70
  - theory1 teoria koko 2
  - theory0 teoria koko 10
  - artikkeli: theory0, 1 ja 7
  - artikkeli: theory0, 10 ja 106
  - teoria: theory0, pöytä, 0 ja 0
  - artikkeli: theory0, 12 ja 150
  - theory2 teoria koko 3
  - theory3 teoria koko 2
  - artikkeli: theory0, 0 ja 6
  - teoria: theory3, square, 3 ja 6
Tieto:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Säännöt:
  - sääntö teoria tulla häviötön joss se ennakoida jokainen havainnointi täsmälleen
  - sääntö valita häviötön teoria vaille vähin koko
Semantiikka: linear muotoilla y = p1 * x + p2; square muotoilla y = x * x + p2; constant muotoilla y = p2; pöytä muotoilla y = entry(x).
Mikä smallest häviötön teoria?

候选项如下：
  - 的理论是：theory1、square、2和4
  - 的理论是：theory2、linear、4和-5
  - 的条目是：theory0、8和70
  - theory1的理论规模是2
  - theory0的理论规模是10
  - 的条目是：theory0、1和7
  - 的条目是：theory0、10和106
  - 的理论是：theory0、桌子、0和0
  - 的条目是：theory0、12和150
  - theory2的理论规模是3
  - theory3的理论规模是2
  - 的条目是：theory0、0和6
  - 的理论是：theory3、square、3和6
数据如下：
  - 1观察到7
  - 8观察到70
  - 12观察到150
  - 0观察到6
  - 10观察到106
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

候補者:
  - 理論:theory1, square, 2と4
  - 理論:theory2, linear, 4と-5
  - 項目:theory0, 8と70
  - theory12理論大きさ
  - theory010理論大きさ
  - 項目:theory0, 1と7
  - 項目:theory0, 10と106
  - 理論:theory0, 台, 0と0
  - 項目:theory0, 12と150
  - theory23理論大きさ
  - theory32理論大きさ
  - 項目:theory0, 0と6
  - 理論:theory3, square, 3と6
資料:
  - 17obs
  - 870obs
  - 12150obs
  - 06obs
  - 10106obs
規則:規則:理論れるロスレスiffこれ予言する凡ゆる観察正確に; 規則:選ぶロスレス理論の中の最小の大きさ.
意味論:lineary = p1 * x + p2形作る; squarey = x * x + p2形作る; constanty = p2形作る; 台y = entry(x)形作る.
smallestロスレス理論何と?

Adaylar:
  - kuram: theory1, square, 2 ve 4
  - kuram: theory2, linear, 4 ve -5
  - entry: theory0, 8 ve 70
  - theory1 2 kuram boyut
  - theory0 10 kuram boyut
  - entry: theory0, 1 ve 7
  - entry: theory0, 10 ve 106
  - kuram: theory0, masa, 0 ve 0
  - entry: theory0, 12 ve 150
  - theory2 3 kuram boyut
  - theory3 2 kuram boyut
  - entry: theory0, 0 ve 6
  - kuram: theory3, square, 3 ve 6
Veriler:
  - 1 7 obs
  - 8 70 obs
  - 12 150 obs
  - 0 6 obs
  - 10 106 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

مُرَشَّح:
  - نَظَرِيَّة: theory1، square، 2 وَـ 4
  - نَظَرِيَّة: theory2، linear، 4 وَـ -5
  - مَدْخَل: theory0، 8 وَـ 70
  - نَظَرِيَّة مَقَاس theory1 2
  - نَظَرِيَّة مَقَاس theory0 10
  - مَدْخَل: theory0، 1 وَـ 7
  - مَدْخَل: theory0، 10 وَـ 106
  - نَظَرِيَّة: theory0، طَاوِلَة، 0 وَـ 0
  - مَدْخَل: theory0، 12 وَـ 150
  - نَظَرِيَّة مَقَاس theory2 3
  - نَظَرِيَّة مَقَاس theory3 2
  - مَدْخَل: theory0، 0 وَـ 6
  - نَظَرِيَّة: theory3، square، 3 وَـ 6
بَيَانَات:
  - obs 1 7
  - obs 8 70
  - obs 12 150
  - obs 0 6
  - obs 10 106
قَانُون:
  - قَانُون نَظَرِيَّة كَانَ lossless iff هُوَ تَنَبَّأَ كُلّ رَصْد بِالضَّبْط
  - قَانُون اِخْتَارَ الـ lossless نَظَرِيَّة مِنْ أَقَلَّ مَقَاس
عِلْم اَلْمَعَانِي: شَكَّلَ linear y = p1 * x + p2؛ شَكَّلَ square y = x * x + p2؛ شَكَّلَ constant y = p2؛ شَكَّلَ الـ طَاوِلَة y = entry(x).
smallest lossless نَظَرِيَّة مَاذَا؟

Კანდიდატები:
  - თეორია: theory1, square, 2 და 4
  - თეორია: theory2, linear, 4 და -5
  - სასათაურო სიტყვა: theory0, 8 და 70
  - theory1 2 თეორია ზომა
  - theory0 10 თეორია ზომა
  - სასათაურო სიტყვა: theory0, 1 და 7
  - სასათაურო სიტყვა: theory0, 10 და 106
  - თეორია: theory0, მაგიდა, 0 და 0
  - სასათაურო სიტყვა: theory0, 12 და 150
  - theory2 3 თეორია ზომა
  - theory3 2 თეორია ზომა
  - სასათაურო სიტყვა: theory0, 0 და 6
  - თეორია: theory3, square, 3 და 6
Მონაცემები:
  - 1 7 obs
  - 8 70 obs
  - 12 150 obs
  - 0 6 obs
  - 10 106 obs
Წესი:
  - წესი თეორია ყოფნა უდანაკარგო iff ის predict ყველა დაკვირვება ზუსტად
  - წესი ამორჩევა უდანაკარგო თეორია of least ზომა
Სემანტიკა: linear y = p1 * x + p2 ბლანკი; square y = x * x + p2 ბლანკი; constant y = p2 ბლანკი; მაგიდა y = entry(x) ბლანკი.
Smallest უდანაკარგო თეორია რა?

Kaiwhakauru:
  - ariā: theory1, square, 2 me 4
  - ariā: theory2, linear, 4 me -5
  - tāurunga: theory0, 8 me 70
  - ariā size theory1 2
  - ariā size theory0 10
  - tāurunga: theory0, 1 me 7
  - tāurunga: theory0, 10 me 106
  - ariā: theory0, tēpu, 0 me 0
  - tāurunga: theory0, 12 me 150
  - ariā size theory2 3
  - ariā size theory3 2
  - tāurunga: theory0, 0 me 6
  - ariā: theory3, square, 3 me 6
Hōtuku:
  - obs 1 7
  - obs 8 70
  - obs 12 150
  - obs 0 6
  - obs 10 106
Rekureihana:
  - rekureihana ariā is lossless iff it matakite every observation pū
  - rekureihana whiri te lossless ariā o least size
Semantics: āhua linear y = p1 * x + p2; āhua square y = x * x + p2; āhua constant y = p2; āhua te tēpu y = entry(x).
Smallest lossless ariā unutai?

Candidates:
  - lý thuyết: theory1, square, 2 và 4
  - lý thuyết: theory2, linear, 4 và -5
  - mục từ: theory0, 8 và 70
  - theory1 lý thuyết kích thước 2
  - theory0 lý thuyết kích thước 10
  - mục từ: theory0, 1 và 7
  - mục từ: theory0, 10 và 106
  - lý thuyết: theory0, bàn, 0 và 0
  - mục từ: theory0, 12 và 150
  - theory2 lý thuyết kích thước 3
  - theory3 lý thuyết kích thước 2
  - mục từ: theory0, 0 và 6
  - lý thuyết: theory3, square, 3 và 6
Dữ liệu:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Quy tắc:
  - quy tắc lý thuyết được lossless iff nó dự báo mỗi observation đúng rồi
  - quy tắc chọn the lossless lý thuyết bằng least kích thước
Ngữ nghĩa: linear làm thành y = p1 * x + p2; square làm thành y = x * x + p2; constant làm thành y = p2; bàn làm thành y = entry(x).
Smallest lossless lý thuyết gì?

ผู้สมัคร:
  - ทฤษฎี:theory1, square, 2และ4
  - ทฤษฎี:theory2, linear, 4และ-5
  - entry:theory0, 8และ70
  - theory1ทฤษฎีขนาด2
  - theory0ทฤษฎีขนาด10
  - entry:theory0, 1และ7
  - entry:theory0, 10และ106
  - ทฤษฎี:theory0, โต๊ะ, 0และ0
  - entry:theory0, 12และ150
  - theory2ทฤษฎีขนาด3
  - theory3ทฤษฎีขนาด2
  - entry:theory0, 0และ6
  - ทฤษฎี:theory3, square, 3และ6
ข้อมูล:
  - 1obs7
  - 8obs70
  - 12obs150
  - 0obs6
  - 10obs106
กฎ:กฎ:ทฤษฎีถูกlosslessiffมันทำนายทุกการสังเกตexactly; กฎ:เลือกlosslessทฤษฎีของleastขนาด.
อรรถศาสตร์:linearรูปร่างy = p1 * x + p2; squareรูปร่างy = x * x + p2; constantรูปร่างy = p2; โต๊ะรูปร่างy = entry(x).
smallestlosslessทฤษฎีอะไร?

வேட்பாளர்:
  - theory: theory1, square, 2 மற்றும் 4
  - theory: theory2, linear, 4 மற்றும் -5
  - உள்நுழைவதற்கு அனுமதி: theory0, 8 மற்றும் 70
  - theory1 2 theory size
  - theory0 10 theory size
  - உள்நுழைவதற்கு அனுமதி: theory0, 1 மற்றும் 7
  - உள்நுழைவதற்கு அனுமதி: theory0, 10 மற்றும் 106
  - theory: theory0, மேசை, 0 மற்றும் 0
  - உள்நுழைவதற்கு அனுமதி: theory0, 12 மற்றும் 150
  - theory2 3 theory size
  - theory3 2 theory size
  - உள்நுழைவதற்கு அனுமதி: theory0, 0 மற்றும் 6
  - theory: theory3, square, 3 மற்றும் 6
தரவுகள்:
  - 1 7 obs
  - 8 70 obs
  - 12 150 obs
  - 0 6 obs
  - 10 106 obs
rules: rule theory படு lossless iff it கணி ஒவ்வொரு observation exactly; rule choose lossless theory கொண்ட least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; மேசை y = entry(x) form.
smallest lossless theory என்ன?

Wagombea ni:
  - theory: theory1, square, 2 na 4
  - theory: theory2, linear, 4 na -5
  - entry: theory0, 8 na 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 na 7
  - entry: theory0, 10 na 106
  - theory: theory0, meza, 0 na 0
  - entry: theory0, 12 na 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 na 6
  - theory: theory3, square, 3 na 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

Candidates:
  - theory: theory1, square, 2 dóó 4
  - theory: theory2, linear, 4 dóó -5
  - entry: theory0, 8 dóó 70
  - theory1 2 theory size
  - theory0 10 theory size
  - entry: theory0, 1 dóó 7
  - entry: theory0, 10 dóó 106
  - theory: theory0, bikááʼ adání, 0 dóó 0
  - entry: theory0, 12 dóó 150
  - theory2 3 theory size
  - theory3 2 theory size
  - entry: theory0, 0 dóó 6
  - theory: theory3, square, 3 dóó 6
Data:
  - 1 7 obs
  - 8 70 obs
  - 12 150 obs
  - 0 6 obs
  - 10 106 obs
Bee hazʼáanii:
  - bee hazʼáanii theory átʼé lossless iff it predict every observation exactly
  - bee hazʼáanii choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; bikááʼ adání y = entry(x) form.
Smallest lossless theory haʼátʼíísh?

Candidates:
  - theory: theory1, square, 2 aamma 4
  - theory: theory2, linear, 4 aamma -5
  - entry: theory0, 8 aamma 70
  - theory1 2 theory size
  - theory0 10 theory size
  - entry: theory0, 1 aamma 7
  - entry: theory0, 10 aamma 106
  - theory: theory0, table, 0 aamma 0
  - entry: theory0, 12 aamma 150
  - theory2 3 theory size
  - theory3 2 theory size
  - entry: theory0, 0 aamma 6
  - theory: theory3, square, 3 aamma 6
Data:
  - 1 7 obs
  - 8 70 obs
  - 12 150 obs
  - 0 6 obs
  - 10 106 obs
Rules: rule theory a lossless iff una predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 blanketti; square y = x * x + p2 blanketti; constant y = p2 blanketti; table y = entry(x) blanketti.
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 2 na 4
  - theory: theory2, linear, 4 na -5
  - entry: theory0, 8 na 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 na 7
  - entry: theory0, 10 na 106
  - theory: theory0, table, 0 na 0
  - entry: theory0, 12 na 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 na 6
  - theory: theory3, square, 3 na 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory bilong least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 2 4
  - theory: theory2, linear, 4 -5
  - entry: theory0, 8 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 7
  - entry: theory0, 10 106
  - theory: theory0, table, 0 0
  - entry: theory0, 12 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 6
  - theory: theory3, square, 3 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Nikanixi:
  - nikanixi theory is lossless iff it predict every observation exactly
  - nikanixi choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory kwèch?

Candidates:
  - theory: theory1, square, 2 а 4
  - theory: theory2, linear, 4 а -5
  - entry: theory0, 8 а 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 а 7
  - entry: theory0, 10 а 106
  - theory: theory0, table, 0 а 0
  - entry: theory0, 12 а 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 а 6
  - theory: theory3, square, 3 а 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Rules:
  - rule theory хила lossless iff it predict дерриг observation exactly
  - rule хержа lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory фу?

후보자:
  - 이론: theory1, square, 2 4
  - 이론: theory2, linear, 4 -5
  - 항목: theory0, 8 70
  - theory1 2 이론 크기
  - theory0 10 이론 크기
  - 항목: theory0, 1 7
  - 항목: theory0, 10 106
  - 이론: theory0, 테이블, 0 0
  - 항목: theory0, 12 150
  - theory2 3 이론 크기
  - theory3 2 이론 크기
  - 항목: theory0, 0 6
  - 이론: theory3, square, 3 6
자료:
  - 1 7 obs
  - 8 70 obs
  - 12 150 obs
  - 0 6 obs
  - 10 106 obs
규칙: 규칙 이론 is lossless iff 이것 예언하다 각 관찰 정확하게; 규칙 고르다 lossless 이론...의 가장 적게 크기.
의미론: linear y = p1 * x + p2 형상; square y = x * x + p2 형상; constant y = p2 형상; 테이블 y = entry(x) 형상.
smallest lossless 이론 무엇?

Kandidatu:
  - theory: theory1, square, 2 eta 4
  - theory: theory2, linear, 4 eta -5
  - sarrera: theory0, 8 eta 70
  - theory1 2 theory tamaina
  - theory0 10 theory tamaina
  - sarrera: theory0, 1 eta 7
  - sarrera: theory0, 10 eta 106
  - theory: theory0, mahai, 0 eta 0
  - sarrera: theory0, 12 eta 150
  - theory2 3 theory tamaina
  - theory3 2 theory tamaina
  - sarrera: theory0, 0 eta 6
  - theory: theory3, square, 3 eta 6
Data:
  - 1 7 obs
  - 8 70 obs
  - 12 150 obs
  - 0 6 obs
  - 10 106 obs
Arau:
  - arau bat theory izan lossless iff it aurresan every observation exactly
  - arau aukeratu the lossless theory of least tamaina
Semantics: linear y = p1 * x + p2 forma; square y = x * x + p2 forma; constant y = p2 forma; mahai y = entry(x) forma.
Smallest lossless theory zer?

ᎠᏙᎩᏯᏍᎩ:
  - theory: theory1, square, 2 ᎠᎴ 4
  - theory: theory2, linear, 4 ᎠᎴ -5
  - entry: theory0, 8 ᎠᎴ 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 ᎠᎴ 7
  - entry: theory0, 10 ᎠᎴ 106
  - theory: theory0, ᎦᏍᎩᎶ, 0 ᎠᎴ 0
  - entry: theory0, 12 ᎠᎴ 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 ᎠᎴ 6
  - theory: theory3, square, 3 ᎠᎴ 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ᎦᏍᎩᎶ form y = entry(x).
What smallest lossless theory?

Candidates:
  - theory: theory1, square, 2 4
  - theory: theory2, linear, 4 -5
  - entry: theory0, 8 70
  - theory1 theory chhika 2
  - theory0 theory chhika 10
  - entry: theory0, 1 7
  - entry: theory0, 10 106
  - theory: theory0, patacha, 0 0
  - entry: theory0, 12 150
  - theory2 theory chhika 3
  - theory3 theory chhika 2
  - entry: theory0, 0 6
  - theory: theory3, square, 3 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Rules:
  - rule theory tiyay lossless iff it predict tukuy observation exactly
  - rule akllay lossless theory of least chhika
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; patacha form y = entry(x).
Smallest lossless theory what?

Candidates:
  - тиориэ: theory1, square, 2 ыкӏи 4
  - тиориэ: theory2, linear, 4 ыкӏи -5
  - entry: theory0, 8 ыкӏи 70
  - theory1 2 тиориэ size
  - theory0 10 тиориэ size
  - entry: theory0, 1 ыкӏи 7
  - entry: theory0, 10 ыкӏи 106
  - тиориэ: theory0, table, 0 ыкӏи 0
  - entry: theory0, 12 ыкӏи 150
  - theory2 3 тиориэ size
  - theory3 2 тиориэ size
  - entry: theory0, 0 ыкӏи 6
  - тиориэ: theory3, square, 3 ыкӏи 6
Data:
  - 1 7 obs
  - 8 70 obs
  - 12 150 obs
  - 0 6 obs
  - 10 106 obs
Rules: rule тиориэ is lossless iff it predict every observation exactly; rule choose the lossless тиориэ of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless тиориэ сыд?

Candidates:
  - theory: theory1, square, 2 thiab 4
  - theory: theory2, linear, 4 thiab -5
  - entry: theory0, 8 thiab 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 thiab 7
  - entry: theory0, 10 thiab 106
  - theory: theory0, rooj, 0 thiab 0
  - entry: theory0, 12 thiab 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 thiab 6
  - theory: theory3, square, 3 thiab 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Cai: cai theory is lossless iff nws predict every observation exactly; cai choose lossless theory of least size.
Lub ntsiab: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; rooj form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 2 4
  - theory: theory2, linear, 4 -5
  - entry: theory0, 8 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 7
  - entry: theory0, 10 106
  - theory: theory0, table, 0 0
  - entry: theory0, 12 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 6
  - theory: theory3, square, 3 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of wy krook size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory ining-jak?

Candidates:
  - theory: theory1, square, 2 micha' 4
  - theory: theory2, linear, 4 micha' -5
  - entry: theory0, 8 micha' 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 micha' 7
  - entry: theory0, 10 micha' 106
  - theory: theory0, table, 0 micha' 0
  - entry: theory0, 12 micha' 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 micha' 6
  - theory: theory3, square, 3 micha' 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory nanta?

Candidates:
  - theory: theory1, square, 2 カ 4
  - theory: theory2, linear, 4 カ -5
  - entry: theory0, 8 カ 70
  - theory1 2 theory size
  - theory0 10 theory size
  - entry: theory0, 1 カ 7
  - entry: theory0, 10 カ 106
  - theory: theory0, table, 0 カ 0
  - entry: theory0, 12 カ 150
  - theory2 3 theory size
  - theory3 2 theory size
  - entry: theory0, 0 カ 6
  - theory: theory3, square, 3 カ 6
Data:
  - 1 7 obs
  - 8 70 obs
  - 12 150 obs
  - 0 6 obs
  - 10 106 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 ノカ; square y = x * x + p2 ノカ; constant y = p2 ノカ; table y = entry(x) ノカ.
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 2 ынкъам 4
  - theory: theory2, linear, 4 ынкъам -5
  - entry: theory0, 8 ынкъам 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 ынкъам 7
  - entry: theory0, 10 ынкъам 106
  - theory: theory0, table, 0 ынкъам 0
  - entry: theory0, 12 ынкъам 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 ынкъам 6
  - theory: theory3, square, 3 ынкъам 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 2 yéetel 4
  - theory: theory2, linear, 4 yéetel -5
  - entry: theory0, 8 yéetel 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 yéetel 7
  - entry: theory0, 10 yéetel 106
  - theory: theory0, table, 0 yéetel 0
  - entry: theory0, 12 yéetel 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 yéetel 6
  - theory: theory3, square, 3 yéetel 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Rules:
  - rule theory yan lossless iff it predict every observation exactly
  - rule yéey lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 2 4
  - theory: theory2, linear, 4 -5
  - entry: theory0, 8 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 7
  - entry: theory0, 10 106
  - theory: theory0, mę́soną, 0 0
  - entry: theory0, 12 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 6
  - theory: theory3, square, 3 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Rules:
  - rule theory is lossless iff ą́wąną predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mę́soną form y = entry(x).
Smallest lossless theory híli?

Candidates:
  - theory: theory1, square, 2 na 4
  - theory: theory2, linear, 4 na -5
  - entry: theory0, 8 na 70
  - theory1 2 theory size
  - theory0 10 theory size
  - entry: theory0, 1 na 7
  - entry: theory0, 10 na 106
  - theory: theory0, table, 0 na 0
  - entry: theory0, 12 na 150
  - theory2 3 theory size
  - theory3 2 theory size
  - entry: theory0, 0 na 6
  - theory: theory3, square, 3 na 6
Data:
  - 1 7 obs
  - 8 70 obs
  - 12 150 obs
  - 0 6 obs
  - 10 106 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 2 4
  - theory: theory2, linear, 4 -5
  - entry: theory0, 8 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 7
  - entry: theory0, 10 106
  - theory: theory0, table, 0 0
  - entry: theory0, 12 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 6
  - theory: theory3, square, 3 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 2 4
  - theory: theory2, linear, 4 -5
  - entry: theory0, 8 70
  - theory1 2 theory size
  - theory0 10 theory size
  - entry: theory0, 1 7
  - entry: theory0, 10 106
  - theory: theory0, table, 0 0
  - entry: theory0, 12 150
  - theory2 3 theory size
  - theory3 2 theory size
  - entry: theory0, 0 6
  - theory: theory3, square, 3 6
Data:
  - 1 7 obs
  - 8 70 obs
  - 12 150 obs
  - 0 6 obs
  - 10 106 obs
Rules:
  - rule maya theory is lossless iff it predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 2 ǂʻá 4
  - theory: theory2, linear, 4 ǂʻá -5
  - entry: theory0, 8 ǂʻá 70
  - theory1 theory ʻǁnàhã 2
  - theory0 theory ʻǁnàhã 10
  - entry: theory0, 1 ǂʻá 7
  - entry: theory0, 10 ǂʻá 106
  - theory: theory0, table, 0 ǂʻá 0
  - entry: theory0, 12 ǂʻá 150
  - theory2 theory ʻǁnàhã 3
  - theory3 theory ʻǁnàhã 2
  - entry: theory0, 0 ǂʻá 6
  - theory: theory3, square, 3 ǂʻá 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Rules:
  - rule theory ǀîi lossless iff èh predict every observation exactly
  - rule choose lossless theory of least ʻǁnàhã
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 2 4
  - theory: theory2, linear, 4 -5
  - entry: theory0, 8 70
  - theory1 2 theory size
  - theory0 10 theory size
  - entry: theory0, 1 7
  - entry: theory0, 10 106
  - theory: theory0, остол, 0 0
  - entry: theory0, 12 150
  - theory2 3 theory size
  - theory3 2 theory size
  - entry: theory0, 0 6
  - theory: theory3, square, 3 6
Data:
  - 1 7 obs
  - 8 70 obs
  - 12 150 obs
  - 0 6 obs
  - 10 106 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; остол y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 2 4
  - theory: theory2, linear, 4 -5
  - entry: theory0, 8 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 7
  - entry: theory0, 10 106
  - theory: theory0, table, 0 0
  - entry: theory0, 12 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 6
  - theory: theory3, square, 3 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 2 4
  - theory: theory2, linear, 4 -5
  - entry: theory0, 8 70
  - theory1 2 theory size
  - theory0 10 theory size
  - entry: theory0, 1 7
  - entry: theory0, 10 106
  - theory: theory0, table, 0 0
  - entry: theory0, 12 150
  - theory2 3 theory size
  - theory3 2 theory size
  - entry: theory0, 0 6
  - theory: theory3, square, 3 6
Data:
  - 1 7 obs
  - 8 70 obs
  - 12 150 obs
  - 0 6 obs
  - 10 106 obs
Rules:
  - rule theory is lossless iff kitu predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 2 4
  - theory: theory2, linear, 4 -5
  - entry: theory0, 8 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 7
  - entry: theory0, 10 106
  - theory: theory0, mesa, 0 0
  - entry: theory0, 12 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 6
  - theory: theory3, square, 3 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mesa form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 2 4
  - theory: theory2, linear, 4 -5
  - entry: theory0, 8 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 7
  - entry: theory0, 10 106
  - theory: theory0, table, 0 0
  - entry: theory0, 12 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 6
  - theory: theory3, square, 3 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Rules:
  - rule theory nemi lossless iff yaja predict every observation exactly
  - rule choose ne lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ne table form y = entry(x).
Smallest lossless theory tay?

Les candidats sont:
  - théorie: theory1, square, 2 et 4
  - théorie: theory2, linear, 4 et -5
  - article: theory0, 8 et 70
  - theory1 théorie taille 2
  - theory0 théorie taille 10
  - article: theory0, 1 et 7
  - article: theory0, 10 et 106
  - théorie: theory0, table, 0 et 0
  - article: theory0, 12 et 150
  - theory2 théorie taille 3
  - theory3 théorie taille 2
  - article: theory0, 0 et 6
  - théorie: theory3, square, 3 et 6
Les données sont:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Les règles sont:
  - règle un théorie être lossless ssi il prédire tout observation exactement
  - règle choisir le lossless théorie du moindre taille
La sémantique est : linear former y = p1 * x + p2 ; square former y = x * x + p2 ; constant former y = p2 ; la table former y = entry(x).
Quoi smallest lossless théorie ?

Kandidato:
  - teorio: theory1, square, 2 kaj 4
  - teorio: theory2, linear, 4 kaj -5
  - entry: theory0, 8 kaj 70
  - theory1 teorio grandeco 2
  - theory0 teorio grandeco 10
  - entry: theory0, 1 kaj 7
  - entry: theory0, 10 kaj 106
  - teorio: theory0, tablo, 0 kaj 0
  - entry: theory0, 12 kaj 150
  - theory2 teorio grandeco 3
  - theory3 teorio grandeco 2
  - entry: theory0, 0 kaj 6
  - teorio: theory3, square, 3 kaj 6
Datumo:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Regulo: regulo teorio egali lossless iff ĝi predict ĉiu observo ekzakte; regulo elekti lossless teorio de plej malmulta grandeco.
Semantics: linear formi y = p1 * x + p2; square formi y = x * x + p2; constant formi y = p2; tablo formi y = entry(x).
Smallest lossless teorio kio?

Indulók:
  - elmélet: theory1, square, 2 és 4
  - elmélet: theory2, linear, 4 és -5
  - szócikk: theory0, 8 és 70
  - theory1 elmélet méret 2
  - theory0 elmélet méret 10
  - szócikk: theory0, 1 és 7
  - szócikk: theory0, 10 és 106
  - elmélet: theory0, asztal, 0 és 0
  - szócikk: theory0, 12 és 150
  - theory2 elmélet méret 3
  - theory3 elmélet méret 2
  - szócikk: theory0, 0 és 6
  - elmélet: theory3, square, 3 és 6
Adat:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Szabályok:
  - szabály elmélet van veszteségmentes acsa az megjósol minden megfigyelés pontosan
  - szabály kiválaszt a veszteségmentes elmélet of legkisebb méret
Szemantika: linear kialakít y = p1 * x + p2; square kialakít y = x * x + p2; constant kialakít y = p2; a asztal kialakít y = entry(x).
Smallest veszteségmentes elmélet melyik?

候選人:
  - theory:theory1, square, 2及4
  - theory:theory2, linear, 4及-5
  - entry:theory0, 8及70
  - theory1theory size2
  - theory0theory size10
  - entry:theory0, 1及7
  - entry:theory0, 10及106
  - theory:theory0, 檯, 0及0
  - entry:theory0, 12及150
  - theory2theory size3
  - theory3theory size2
  - entry:theory0, 0及6
  - theory:theory3, square, 3及6
數據:
  - 1obs7
  - 8obs70
  - 12obs150
  - 0obs6
  - 10obs106
rules:rule:一theory是losslessiffitpredict每observationexactly; rule:揀losslesstheory...嘅leastsize.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; 檯formy = entry(x).
smallest lossless theory乜嘢?

Candidates:
  - theory: theory1, square, 2 とぅ 4
  - theory: theory2, linear, 4 とぅ -5
  - entry: theory0, 8 とぅ 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 とぅ 7
  - entry: theory0, 10 とぅ 106
  - theory: theory0, table, 0 とぅ 0
  - entry: theory0, 12 とぅ 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 とぅ 6
  - theory: theory3, square, 3 とぅ 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Rules: rule theory 有ん lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Үміткер:
  - теория: theory1, square, 2 және 4
  - теория: theory2, linear, 4 және -5
  - entry: theory0, 8 және 70
  - theory1 теория мөлшер 2
  - theory0 теория мөлшер 10
  - entry: theory0, 1 және 7
  - entry: theory0, 10 және 106
  - теория: theory0, үстел, 0 және 0
  - entry: theory0, 12 және 150
  - theory2 теория мөлшер 3
  - theory3 теория мөлшер 2
  - entry: theory0, 0 және 6
  - теория: theory3, square, 3 және 6
Деректер:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Ереже: ереже теория is lossless iff ол predict әр бақылау exactly; ереже таңдау lossless теория туралы least мөлшер.
Семантикалық: linear пішін y = p1 * x + p2; square пішін y = x * x + p2; constant пішін y = p2; үстел пішін y = entry(x).
Smallest lossless теория не?

מועמדת:
  - תּוֹרָה: theory1, square, 2 וְ־ 4
  - תּוֹרָה: theory2, linear, 4 וְ־ -5
  - entry: theory0, 8 וְ־ 70
  - theory1 תּוֹרָה גֹּדֶל 2
  - theory0 תּוֹרָה גֹּדֶל 10
  - entry: theory0, 1 וְ־ 7
  - entry: theory0, 10 וְ־ 106
  - תּוֹרָה: theory0, טַבְלָה, 0 וְ־ 0
  - entry: theory0, 12 וְ־ 150
  - theory2 תּוֹרָה גֹּדֶל 3
  - theory3 תּוֹרָה גֹּדֶל 2
  - entry: theory0, 0 וְ־ 6
  - תּוֹרָה: theory3, square, 3 וְ־ 6
נְתוּנִים:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
מָשַׁל:
  - מָשַׁל אַחַת תּוֹרָה הוא lossless אםם זֶה predict כֹּל תַּצְפִּית בדיוק
  - מָשַׁל בחר ה־ lossless תּוֹרָה שֶׁל least גֹּדֶל
תורת המשמעים: linear צורה y = p1 * x + p2; square צורה y = x * x + p2; constant צורה y = p2; טַבְלָה ה־ צורה y = entry(x).
איזה smallest lossless תּוֹרָה?

Candidates:
  - theory: theory1, square, 2 დო 4
  - theory: theory2, linear, 4 დო -5
  - entry: theory0, 8 დო 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 დო 7
  - entry: theory0, 10 დო 106
  - theory: theory0, table, 0 დო 0
  - entry: theory0, 12 დო 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 დო 6
  - theory: theory3, square, 3 დო 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Kandidat:
  - teori: theory1, square, 2 dan 4
  - teori: theory2, linear, 4 dan -5
  - lema: theory0, 8 dan 70
  - theory1 teori ukuran 2
  - theory0 teori ukuran 10
  - lema: theory0, 1 dan 7
  - lema: theory0, 10 dan 106
  - teori: theory0, meja, 0 dan 0
  - lema: theory0, 12 dan 150
  - theory2 teori ukuran 3
  - theory3 teori ukuran 2
  - lema: theory0, 0 dan 6
  - teori: theory3, square, 3 dan 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Rules:
  - rule teori berada lossless iff it predict setiap observation tepat
  - rule memilih si lossless teori dari least ukuran
Semantik: linear formulir y = p1 * x + p2; square formulir y = x * x + p2; constant formulir y = p2; meja si formulir y = entry(x).
Smallest lossless teori apa?

បេក្ខជន:
  - ទ្រឹស្ដី:theory1, square, 2នឹង4
  - ទ្រឹស្ដី:theory2, linear, 4នឹង-5
  - មេពាក្យ:theory0, 8នឹង70
  - theory1ទ្រឹស្ដីទំហំ2
  - theory0ទ្រឹស្ដីទំហំ10
  - មេពាក្យ:theory0, 1នឹង7
  - មេពាក្យ:theory0, 10នឹង106
  - ទ្រឹស្ដី:theory0, តុ, 0នឹង0
  - មេពាក្យ:theory0, 12នឹង150
  - theory2ទ្រឹស្ដីទំហំ3
  - theory3ទ្រឹស្ដីទំហំ2
  - មេពាក្យ:theory0, 0នឹង6
  - ទ្រឹស្ដី:theory3, square, 3នឹង6
ទិន្នន័យ:
  - 1obs7
  - 8obs70
  - 12obs150
  - 0obs6
  - 10obs106
ក្បួន:ក្បួន:ទ្រឹស្ដីត្រូវបានlosslessiffវាចាប់យាមរាល់គំនន់exactly; ក្បួន:រើសthelosslessទ្រឹស្ដីនៃleastទំហំ.
និឃណ្ដសាស្ត្រ:linearគ្រោងy = p1 * x + p2; squareគ្រោងy = x * x + p2; constantគ្រោងy = p2; តុគ្រោងy = entry(x).
smallestlosslessទ្រឹស្ដីអី?

ຜູ້ສະໝັກ:
  - ທິດສະດີ:theory1, square, 2ແລະ4
  - ທິດສະດີ:theory2, linear, 4ແລະ-5
  - entry:theory0, 8ແລະ70
  - theory1ທິດສະດີຂະຫນາດ2
  - theory0ທິດສະດີຂະຫນາດ10
  - entry:theory0, 1ແລະ7
  - entry:theory0, 10ແລະ106
  - ທິດສະດີ:theory0, ໂຕະ, 0ແລະ0
  - entry:theory0, 12ແລະ150
  - theory2ທິດສະດີຂະຫນາດ3
  - theory3ທິດສະດີຂະຫນາດ2
  - entry:theory0, 0ແລະ6
  - ທິດສະດີ:theory3, square, 3ແລະ6
ຂໍ້ມູນ:
  - 1obs7
  - 8obs70
  - 12obs150
  - 0obs6
  - 10obs106
ກະຕິກາ:ກະຕິກາ:ທິດສະດີຢູ່losslessiffມັນທຳນວາຍທຸກobservationexactly; ກະຕິກາ:ເລືອກlosslessທິດສະດີຂອງleastຂະຫນາດ.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; ໂຕະformy = entry(x).
smallestlosslessທິດສະດີຫຍັງ?

candidates:
  - theory: theory1, square, 2 మరియు 4
  - theory: theory2, linear, 4 మరియు -5
  - entry: theory0, 8 మరియు 70
  - theory1 2 theory size
  - theory0 10 theory size
  - entry: theory0, 1 మరియు 7
  - entry: theory0, 10 మరియు 106
  - theory: theory0, బల్ల, 0 మరియు 0
  - entry: theory0, 12 మరియు 150
  - theory2 3 theory size
  - theory3 2 theory size
  - entry: theory0, 0 మరియు 6
  - theory: theory3, square, 3 మరియు 6
data:
  - 1 7 obs
  - 8 70 obs
  - 12 150 obs
  - 0 6 obs
  - 10 106 obs
నియమం: నియమం theory ఉండు lossless iff it predict ప్రతి పరిశీలన exactly; నియమం choose lossless theory of least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; బల్ల y = entry(x) form.
smallest lossless theory ఏమిటి?

Candidates:
  - theory: theory1, square, 2 4
  - theory: theory2, linear, 4 -5
  - entry: theory0, 8 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 7
  - entry: theory0, 10 106
  - theory: theory0, table, 0 0
  - entry: theory0, 12 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 6
  - theory: theory3, square, 3 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Rules: rule theory wà lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
What smallest lossless theory?

Candidates:
  - theory: theory1, square, 2 4
  - theory: theory2, linear, 4 -5
  - entry: theory0, 8 70
  - theory1 2 theory size
  - theory0 10 theory size
  - entry: theory0, 1 7
  - entry: theory0, 10 106
  - theory: theory0, table, 0 0
  - entry: theory0, 12 150
  - theory2 3 theory size
  - theory3 2 theory size
  - entry: theory0, 0 6
  - theory: theory3, square, 3 6
Data:
  - 1 7 obs
  - 8 70 obs
  - 12 150 obs
  - 0 6 obs
  - 10 106 obs
Rules:
  - rule theory naiágúóli lossless iff it predict every observation exactly
  - rule choose the lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

candidates:
  - theory: theory1, square, 2 4
  - theory: theory2, linear, 4 -5
  - entry: theory0, 8 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 7
  - entry: theory0, 10 106
  - theory: theory0, table, 0 0
  - entry: theory0, 12 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 6
  - theory: theory3, square, 3 6
data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
smallest lossless theory what?

Candidates:
  - theory: theory1, square, 2 4
  - theory: theory2, linear, 4 -5
  - entry: theory0, 8 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 7
  - entry: theory0, 10 106
  - theory: theory0, tafra, 0 0
  - entry: theory0, 12 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 6
  - theory: theory3, square, 3 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; tafra form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 2 4
  - theory: theory2, linear, 4 -5
  - entry: theory0, 8 70
  - theory1 theory size 2
  - theory0 theory size 10
  - entry: theory0, 1 7
  - entry: theory0, 10 106
  - theory: theory0, táxemésėhestȯtse, 0 0
  - entry: theory0, 12 150
  - theory2 theory size 3
  - theory3 theory size 2
  - entry: theory0, 0 6
  - theory: theory3, square, 3 6
Data:
  - 1 obs 7
  - 8 obs 70
  - 12 obs 150
  - 0 obs 6
  - 10 obs 106
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; táxemésėhestȯtse form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory1, square, 2 4
  - theory: theory2, linear, 4 -5
  - entry: theory0, 8 70
  - theory1 2 theory size
  - theory0 10 theory size
  - entry: theory0, 1 7
  - entry: theory0, 10 106
  - theory: theory0, ствал, 0 0
  - entry: theory0, 12 150
  - theory2 3 theory size
  - theory3 2 theory size
  - entry: theory0, 0 6
  - theory: theory3, square, 3 6
Data:
  - 1 7 obs
  - 8 70 obs
  - 12 150 obs
  - 0 6 obs
  - 10 106 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; ствал y = entry(x) form.
Smallest lossless theory вуч?

The candidates are:
  - entry: theory3, 1 and 10
  - entry: theory3, 2 and 14
  - theory: theory2, square, 3 and 0
  - entry: theory3, 12 and 54
  - theory1 theory size 3
  - entry: theory3, 3 and 18
  - entry: theory3, 0 and 6
  - theory: theory1, linear, 6 and 4
  - theory: theory0, linear, 4 and 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, table, 0 and 0
The data are:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

Los candidatos son:
  - la entrada: theory3, 1 y 10
  - la entrada: theory3, 2 y 14
  - la teoría: theory2, square, 3 y 0
  - la entrada: theory3, 12 y 54
  - theory1 el tamaño de la teoría 3
  - la entrada: theory3, 3 y 18
  - la entrada: theory3, 0 y 6
  - la teoría: theory1, linear, 6 y 4
  - la teoría: theory0, linear, 4 y 6
  - theory2 el tamaño de la teoría 2
  - theory3 el tamaño de la teoría 10
  - theory0 el tamaño de la teoría 3
  - la teoría: theory3, mesa, 0 y 0
Los datos son:
  - 3 la observación 18
  - 2 la observación 14
  - 0 la observación 6
  - 12 la observación 54
  - 1 la observación 10
Las reglas son:
  - la regla: a la teoría es lossless si y sólo si it predice every observation exactamente
  - la regla: choose el lossless la teoría de least tamaño
La semántica es: linear la forma y = p1 * x + p2; square la forma y = x * x + p2; constant la forma y = p2; la mesa la forma y = entry(x).
¿Qué smallest lossless la teoría?

候选项如下：
  - 的条目是：theory3、1和10
  - 的条目是：theory3、2和14
  - 的理论是：theory2、square、3和0
  - 的条目是：theory3、12和54
  - theory1的理论规模是3
  - 的条目是：theory3、3和18
  - 的条目是：theory3、0和6
  - 的理论是：theory1、linear、6和4
  - 的理论是：theory0、linear、4和6
  - theory2的理论规模是2
  - theory3的理论规模是10
  - theory0的理论规模是3
  - 的理论是：theory3、桌子、0和0
数据如下：
  - 3观察到18
  - 2观察到14
  - 0观察到6
  - 12观察到54
  - 1观察到10
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

Adaylar:
  - entry: theory3, 1 ve 10
  - entry: theory3, 2 ve 14
  - kuram: theory2, square, 3 ve 0
  - entry: theory3, 12 ve 54
  - theory1 3 kuram boyut
  - entry: theory3, 3 ve 18
  - entry: theory3, 0 ve 6
  - kuram: theory1, linear, 6 ve 4
  - kuram: theory0, linear, 4 ve 6
  - theory2 2 kuram boyut
  - theory3 10 kuram boyut
  - theory0 3 kuram boyut
  - kuram: theory3, masa, 0 ve 0
Veriler:
  - 3 18 obs
  - 2 14 obs
  - 0 6 obs
  - 12 54 obs
  - 1 10 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

Wagombea ni:
  - entry: theory3, 1 na 10
  - entry: theory3, 2 na 14
  - theory: theory2, square, 3 na 0
  - entry: theory3, 12 na 54
  - theory1 theory size 3
  - entry: theory3, 3 na 18
  - entry: theory3, 0 na 6
  - theory: theory1, linear, 6 na 4
  - theory: theory0, linear, 4 na 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, meza, 0 na 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

The candidates are:
  - entry: theory3, 1 and 10
  - entry: theory3, 2 and 14
  - theory: theory2, square, 3 and 0
  - entry: theory3, 12 and 54
  - theory1 theory size 3
  - entry: theory3, 3 and 18
  - entry: theory3, 0 and 6
  - theory: theory1, linear, 6 and 4
  - theory: theory0, linear, 4 and 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, table, 0 and 0
The data are:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

{candidates: [(entry theory3 1 10) (entry theory3 2 14) (theory theory2 square 3 0) (entry theory3 12 54) (theory_size theory1 3) (entry theory3 3 18) (entry theory3 0 6) (theory theory1 linear 6 4) (theory theory0 linear 4 6) (theory_size theory2 2) (theory_size theory3 10) (theory_size theory0 3) (theory theory3 table 0 0)], data: [(obs 3 18) (obs 2 14) (obs 0 6) (obs 12 54) (obs 1 10)], query: smallest_lossless_theory, rules: [(rule (a_theory_is_lossless_iff_it_predicts_every_observation_exactly)) (rule (choose_the_lossless_theory_of_least_size))], semantics: [(form linear "y = p1 * x + p2") (form square "y = x * x + p2") (form constant "y = p2") (form table "y = entry(x)")]}

Die Kandidaten sind:
  - Eintrag: theory3, 1 und 10
  - Eintrag: theory3, 2 und 14
  - Theorie: theory2, square, 3 und 0
  - Eintrag: theory3, 12 und 54
  - theory1 Theorie Größe 3
  - Eintrag: theory3, 3 und 18
  - Eintrag: theory3, 0 und 6
  - Theorie: theory1, linear, 6 und 4
  - Theorie: theory0, linear, 4 und 6
  - theory2 Theorie Größe 2
  - theory3 Theorie Größe 10
  - theory0 Theorie Größe 3
  - Theorie: theory3, Tisch, 0 und 0
Die Daten sind:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Die Regeln sind:
  - Regel ein Theorie werden verlustfrei gdw. er vorhersagen jeder Beobachtung genau
  - Regel wählen der verlustfrei Theorie aus geringst Größe
Die Semantik ist: linear formen y = p1 * x + p2; square formen y = x * x + p2; constant formen y = p2; der Tisch formen y = entry(x).
Was smallest verlustfrei Theorie?

Кандѝда̄т:
  - одредница: theory3, 1 и 10
  - одредница: theory3, 2 и 14
  - тѐо̄рија: theory2, square, 3 и 0
  - одредница: theory3, 12 и 54
  - theory1 тѐо̄рија величѝна 3
  - одредница: theory3, 3 и 18
  - одредница: theory3, 0 и 6
  - тѐо̄рија: theory1, linear, 6 и 4
  - тѐо̄рија: theory0, linear, 4 и 6
  - theory2 тѐо̄рија величѝна 2
  - theory3 тѐо̄рија величѝна 10
  - theory0 тѐо̄рија величѝна 3
  - тѐо̄рија: theory3, сто̑л, 0 и 0
Податци:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Пра̏вило:
  - пра̏вило тѐо̄рија би̏ти lossless iff оно predvidjeti сва̏кӣ опа́жа̄ње тачно
  - пра̏вило изабрати lossless тѐо̄рија od minimalan величѝна
Сема̀нтика: linear oblik y = p1 * x + p2; square oblik y = x * x + p2; constant oblik y = p2; сто̑л oblik y = entry(x).
Smallest lossless тѐо̄рија kakav?

Ehdokkaat:
  - artikkeli: theory3, 1 ja 10
  - artikkeli: theory3, 2 ja 14
  - teoria: theory2, square, 3 ja 0
  - artikkeli: theory3, 12 ja 54
  - theory1 teoria koko 3
  - artikkeli: theory3, 3 ja 18
  - artikkeli: theory3, 0 ja 6
  - teoria: theory1, linear, 6 ja 4
  - teoria: theory0, linear, 4 ja 6
  - theory2 teoria koko 2
  - theory3 teoria koko 10
  - theory0 teoria koko 3
  - teoria: theory3, pöytä, 0 ja 0
Tieto:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Säännöt:
  - sääntö teoria tulla häviötön joss se ennakoida jokainen havainnointi täsmälleen
  - sääntö valita häviötön teoria vaille vähin koko
Semantiikka: linear muotoilla y = p1 * x + p2; square muotoilla y = x * x + p2; constant muotoilla y = p2; pöytä muotoilla y = entry(x).
Mikä smallest häviötön teoria?

候选项如下：
  - 的条目是：theory3、1和10
  - 的条目是：theory3、2和14
  - 的理论是：theory2、square、3和0
  - 的条目是：theory3、12和54
  - theory1的理论规模是3
  - 的条目是：theory3、3和18
  - 的条目是：theory3、0和6
  - 的理论是：theory1、linear、6和4
  - 的理论是：theory0、linear、4和6
  - theory2的理论规模是2
  - theory3的理论规模是10
  - theory0的理论规模是3
  - 的理论是：theory3、桌子、0和0
数据如下：
  - 3观察到18
  - 2观察到14
  - 0观察到6
  - 12观察到54
  - 1观察到10
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

候補者:
  - 項目:theory3, 1と10
  - 項目:theory3, 2と14
  - 理論:theory2, square, 3と0
  - 項目:theory3, 12と54
  - theory13理論大きさ
  - 項目:theory3, 3と18
  - 項目:theory3, 0と6
  - 理論:theory1, linear, 6と4
  - 理論:theory0, linear, 4と6
  - theory22理論大きさ
  - theory310理論大きさ
  - theory03理論大きさ
  - 理論:theory3, 台, 0と0
資料:
  - 318obs
  - 214obs
  - 06obs
  - 1254obs
  - 110obs
規則:規則:理論れるロスレスiffこれ予言する凡ゆる観察正確に; 規則:選ぶロスレス理論の中の最小の大きさ.
意味論:lineary = p1 * x + p2形作る; squarey = x * x + p2形作る; constanty = p2形作る; 台y = entry(x)形作る.
smallestロスレス理論何と?

Adaylar:
  - entry: theory3, 1 ve 10
  - entry: theory3, 2 ve 14
  - kuram: theory2, square, 3 ve 0
  - entry: theory3, 12 ve 54
  - theory1 3 kuram boyut
  - entry: theory3, 3 ve 18
  - entry: theory3, 0 ve 6
  - kuram: theory1, linear, 6 ve 4
  - kuram: theory0, linear, 4 ve 6
  - theory2 2 kuram boyut
  - theory3 10 kuram boyut
  - theory0 3 kuram boyut
  - kuram: theory3, masa, 0 ve 0
Veriler:
  - 3 18 obs
  - 2 14 obs
  - 0 6 obs
  - 12 54 obs
  - 1 10 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

مُرَشَّح:
  - مَدْخَل: theory3، 1 وَـ 10
  - مَدْخَل: theory3، 2 وَـ 14
  - نَظَرِيَّة: theory2، square، 3 وَـ 0
  - مَدْخَل: theory3، 12 وَـ 54
  - نَظَرِيَّة مَقَاس theory1 3
  - مَدْخَل: theory3، 3 وَـ 18
  - مَدْخَل: theory3، 0 وَـ 6
  - نَظَرِيَّة: theory1، linear، 6 وَـ 4
  - نَظَرِيَّة: theory0، linear، 4 وَـ 6
  - نَظَرِيَّة مَقَاس theory2 2
  - نَظَرِيَّة مَقَاس theory3 10
  - نَظَرِيَّة مَقَاس theory0 3
  - نَظَرِيَّة: theory3، طَاوِلَة، 0 وَـ 0
بَيَانَات:
  - obs 3 18
  - obs 2 14
  - obs 0 6
  - obs 12 54
  - obs 1 10
قَانُون:
  - قَانُون نَظَرِيَّة كَانَ lossless iff هُوَ تَنَبَّأَ كُلّ رَصْد بِالضَّبْط
  - قَانُون اِخْتَارَ الـ lossless نَظَرِيَّة مِنْ أَقَلَّ مَقَاس
عِلْم اَلْمَعَانِي: شَكَّلَ linear y = p1 * x + p2؛ شَكَّلَ square y = x * x + p2؛ شَكَّلَ constant y = p2؛ شَكَّلَ الـ طَاوِلَة y = entry(x).
smallest lossless نَظَرِيَّة مَاذَا؟

Კანდიდატები:
  - სასათაურო სიტყვა: theory3, 1 და 10
  - სასათაურო სიტყვა: theory3, 2 და 14
  - თეორია: theory2, square, 3 და 0
  - სასათაურო სიტყვა: theory3, 12 და 54
  - theory1 3 თეორია ზომა
  - სასათაურო სიტყვა: theory3, 3 და 18
  - სასათაურო სიტყვა: theory3, 0 და 6
  - თეორია: theory1, linear, 6 და 4
  - თეორია: theory0, linear, 4 და 6
  - theory2 2 თეორია ზომა
  - theory3 10 თეორია ზომა
  - theory0 3 თეორია ზომა
  - თეორია: theory3, მაგიდა, 0 და 0
Მონაცემები:
  - 3 18 obs
  - 2 14 obs
  - 0 6 obs
  - 12 54 obs
  - 1 10 obs
Წესი:
  - წესი თეორია ყოფნა უდანაკარგო iff ის predict ყველა დაკვირვება ზუსტად
  - წესი ამორჩევა უდანაკარგო თეორია of least ზომა
Სემანტიკა: linear y = p1 * x + p2 ბლანკი; square y = x * x + p2 ბლანკი; constant y = p2 ბლანკი; მაგიდა y = entry(x) ბლანკი.
Smallest უდანაკარგო თეორია რა?

Kaiwhakauru:
  - tāurunga: theory3, 1 me 10
  - tāurunga: theory3, 2 me 14
  - ariā: theory2, square, 3 me 0
  - tāurunga: theory3, 12 me 54
  - ariā size theory1 3
  - tāurunga: theory3, 3 me 18
  - tāurunga: theory3, 0 me 6
  - ariā: theory1, linear, 6 me 4
  - ariā: theory0, linear, 4 me 6
  - ariā size theory2 2
  - ariā size theory3 10
  - ariā size theory0 3
  - ariā: theory3, tēpu, 0 me 0
Hōtuku:
  - obs 3 18
  - obs 2 14
  - obs 0 6
  - obs 12 54
  - obs 1 10
Rekureihana:
  - rekureihana ariā is lossless iff it matakite every observation pū
  - rekureihana whiri te lossless ariā o least size
Semantics: āhua linear y = p1 * x + p2; āhua square y = x * x + p2; āhua constant y = p2; āhua te tēpu y = entry(x).
Smallest lossless ariā unutai?

Candidates:
  - mục từ: theory3, 1 và 10
  - mục từ: theory3, 2 và 14
  - lý thuyết: theory2, square, 3 và 0
  - mục từ: theory3, 12 và 54
  - theory1 lý thuyết kích thước 3
  - mục từ: theory3, 3 và 18
  - mục từ: theory3, 0 và 6
  - lý thuyết: theory1, linear, 6 và 4
  - lý thuyết: theory0, linear, 4 và 6
  - theory2 lý thuyết kích thước 2
  - theory3 lý thuyết kích thước 10
  - theory0 lý thuyết kích thước 3
  - lý thuyết: theory3, bàn, 0 và 0
Dữ liệu:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Quy tắc:
  - quy tắc lý thuyết được lossless iff nó dự báo mỗi observation đúng rồi
  - quy tắc chọn the lossless lý thuyết bằng least kích thước
Ngữ nghĩa: linear làm thành y = p1 * x + p2; square làm thành y = x * x + p2; constant làm thành y = p2; bàn làm thành y = entry(x).
Smallest lossless lý thuyết gì?

ผู้สมัคร:
  - entry:theory3, 1และ10
  - entry:theory3, 2และ14
  - ทฤษฎี:theory2, square, 3และ0
  - entry:theory3, 12และ54
  - theory1ทฤษฎีขนาด3
  - entry:theory3, 3และ18
  - entry:theory3, 0และ6
  - ทฤษฎี:theory1, linear, 6และ4
  - ทฤษฎี:theory0, linear, 4และ6
  - theory2ทฤษฎีขนาด2
  - theory3ทฤษฎีขนาด10
  - theory0ทฤษฎีขนาด3
  - ทฤษฎี:theory3, โต๊ะ, 0และ0
ข้อมูล:
  - 3obs18
  - 2obs14
  - 0obs6
  - 12obs54
  - 1obs10
กฎ:กฎ:ทฤษฎีถูกlosslessiffมันทำนายทุกการสังเกตexactly; กฎ:เลือกlosslessทฤษฎีของleastขนาด.
อรรถศาสตร์:linearรูปร่างy = p1 * x + p2; squareรูปร่างy = x * x + p2; constantรูปร่างy = p2; โต๊ะรูปร่างy = entry(x).
smallestlosslessทฤษฎีอะไร?

வேட்பாளர்:
  - உள்நுழைவதற்கு அனுமதி: theory3, 1 மற்றும் 10
  - உள்நுழைவதற்கு அனுமதி: theory3, 2 மற்றும் 14
  - theory: theory2, square, 3 மற்றும் 0
  - உள்நுழைவதற்கு அனுமதி: theory3, 12 மற்றும் 54
  - theory1 3 theory size
  - உள்நுழைவதற்கு அனுமதி: theory3, 3 மற்றும் 18
  - உள்நுழைவதற்கு அனுமதி: theory3, 0 மற்றும் 6
  - theory: theory1, linear, 6 மற்றும் 4
  - theory: theory0, linear, 4 மற்றும் 6
  - theory2 2 theory size
  - theory3 10 theory size
  - theory0 3 theory size
  - theory: theory3, மேசை, 0 மற்றும் 0
தரவுகள்:
  - 3 18 obs
  - 2 14 obs
  - 0 6 obs
  - 12 54 obs
  - 1 10 obs
rules: rule theory படு lossless iff it கணி ஒவ்வொரு observation exactly; rule choose lossless theory கொண்ட least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; மேசை y = entry(x) form.
smallest lossless theory என்ன?

Wagombea ni:
  - entry: theory3, 1 na 10
  - entry: theory3, 2 na 14
  - theory: theory2, square, 3 na 0
  - entry: theory3, 12 na 54
  - theory1 theory size 3
  - entry: theory3, 3 na 18
  - entry: theory3, 0 na 6
  - theory: theory1, linear, 6 na 4
  - theory: theory0, linear, 4 na 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, meza, 0 na 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

Candidates:
  - entry: theory3, 1 dóó 10
  - entry: theory3, 2 dóó 14
  - theory: theory2, square, 3 dóó 0
  - entry: theory3, 12 dóó 54
  - theory1 3 theory size
  - entry: theory3, 3 dóó 18
  - entry: theory3, 0 dóó 6
  - theory: theory1, linear, 6 dóó 4
  - theory: theory0, linear, 4 dóó 6
  - theory2 2 theory size
  - theory3 10 theory size
  - theory0 3 theory size
  - theory: theory3, bikááʼ adání, 0 dóó 0
Data:
  - 3 18 obs
  - 2 14 obs
  - 0 6 obs
  - 12 54 obs
  - 1 10 obs
Bee hazʼáanii:
  - bee hazʼáanii theory átʼé lossless iff it predict every observation exactly
  - bee hazʼáanii choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; bikááʼ adání y = entry(x) form.
Smallest lossless theory haʼátʼíísh?

Candidates:
  - entry: theory3, 1 aamma 10
  - entry: theory3, 2 aamma 14
  - theory: theory2, square, 3 aamma 0
  - entry: theory3, 12 aamma 54
  - theory1 3 theory size
  - entry: theory3, 3 aamma 18
  - entry: theory3, 0 aamma 6
  - theory: theory1, linear, 6 aamma 4
  - theory: theory0, linear, 4 aamma 6
  - theory2 2 theory size
  - theory3 10 theory size
  - theory0 3 theory size
  - theory: theory3, table, 0 aamma 0
Data:
  - 3 18 obs
  - 2 14 obs
  - 0 6 obs
  - 12 54 obs
  - 1 10 obs
Rules: rule theory a lossless iff una predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 blanketti; square y = x * x + p2 blanketti; constant y = p2 blanketti; table y = entry(x) blanketti.
Smallest lossless theory what?

Candidates:
  - entry: theory3, 1 na 10
  - entry: theory3, 2 na 14
  - theory: theory2, square, 3 na 0
  - entry: theory3, 12 na 54
  - theory1 theory size 3
  - entry: theory3, 3 na 18
  - entry: theory3, 0 na 6
  - theory: theory1, linear, 6 na 4
  - theory: theory0, linear, 4 na 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, table, 0 na 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory bilong least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory3, 1 10
  - entry: theory3, 2 14
  - theory: theory2, square, 3 0
  - entry: theory3, 12 54
  - theory1 theory size 3
  - entry: theory3, 3 18
  - entry: theory3, 0 6
  - theory: theory1, linear, 6 4
  - theory: theory0, linear, 4 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, table, 0 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Nikanixi:
  - nikanixi theory is lossless iff it predict every observation exactly
  - nikanixi choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory kwèch?

Candidates:
  - entry: theory3, 1 а 10
  - entry: theory3, 2 а 14
  - theory: theory2, square, 3 а 0
  - entry: theory3, 12 а 54
  - theory1 theory size 3
  - entry: theory3, 3 а 18
  - entry: theory3, 0 а 6
  - theory: theory1, linear, 6 а 4
  - theory: theory0, linear, 4 а 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, table, 0 а 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Rules:
  - rule theory хила lossless iff it predict дерриг observation exactly
  - rule хержа lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory фу?

후보자:
  - 항목: theory3, 1 10
  - 항목: theory3, 2 14
  - 이론: theory2, square, 3 0
  - 항목: theory3, 12 54
  - theory1 3 이론 크기
  - 항목: theory3, 3 18
  - 항목: theory3, 0 6
  - 이론: theory1, linear, 6 4
  - 이론: theory0, linear, 4 6
  - theory2 2 이론 크기
  - theory3 10 이론 크기
  - theory0 3 이론 크기
  - 이론: theory3, 테이블, 0 0
자료:
  - 3 18 obs
  - 2 14 obs
  - 0 6 obs
  - 12 54 obs
  - 1 10 obs
규칙: 규칙 이론 is lossless iff 이것 예언하다 각 관찰 정확하게; 규칙 고르다 lossless 이론...의 가장 적게 크기.
의미론: linear y = p1 * x + p2 형상; square y = x * x + p2 형상; constant y = p2 형상; 테이블 y = entry(x) 형상.
smallest lossless 이론 무엇?

Kandidatu:
  - sarrera: theory3, 1 eta 10
  - sarrera: theory3, 2 eta 14
  - theory: theory2, square, 3 eta 0
  - sarrera: theory3, 12 eta 54
  - theory1 3 theory tamaina
  - sarrera: theory3, 3 eta 18
  - sarrera: theory3, 0 eta 6
  - theory: theory1, linear, 6 eta 4
  - theory: theory0, linear, 4 eta 6
  - theory2 2 theory tamaina
  - theory3 10 theory tamaina
  - theory0 3 theory tamaina
  - theory: theory3, mahai, 0 eta 0
Data:
  - 3 18 obs
  - 2 14 obs
  - 0 6 obs
  - 12 54 obs
  - 1 10 obs
Arau:
  - arau bat theory izan lossless iff it aurresan every observation exactly
  - arau aukeratu the lossless theory of least tamaina
Semantics: linear y = p1 * x + p2 forma; square y = x * x + p2 forma; constant y = p2 forma; mahai y = entry(x) forma.
Smallest lossless theory zer?

ᎠᏙᎩᏯᏍᎩ:
  - entry: theory3, 1 ᎠᎴ 10
  - entry: theory3, 2 ᎠᎴ 14
  - theory: theory2, square, 3 ᎠᎴ 0
  - entry: theory3, 12 ᎠᎴ 54
  - theory1 theory size 3
  - entry: theory3, 3 ᎠᎴ 18
  - entry: theory3, 0 ᎠᎴ 6
  - theory: theory1, linear, 6 ᎠᎴ 4
  - theory: theory0, linear, 4 ᎠᎴ 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, ᎦᏍᎩᎶ, 0 ᎠᎴ 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ᎦᏍᎩᎶ form y = entry(x).
What smallest lossless theory?

Candidates:
  - entry: theory3, 1 10
  - entry: theory3, 2 14
  - theory: theory2, square, 3 0
  - entry: theory3, 12 54
  - theory1 theory chhika 3
  - entry: theory3, 3 18
  - entry: theory3, 0 6
  - theory: theory1, linear, 6 4
  - theory: theory0, linear, 4 6
  - theory2 theory chhika 2
  - theory3 theory chhika 10
  - theory0 theory chhika 3
  - theory: theory3, patacha, 0 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Rules:
  - rule theory tiyay lossless iff it predict tukuy observation exactly
  - rule akllay lossless theory of least chhika
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; patacha form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory3, 1 ыкӏи 10
  - entry: theory3, 2 ыкӏи 14
  - тиориэ: theory2, square, 3 ыкӏи 0
  - entry: theory3, 12 ыкӏи 54
  - theory1 3 тиориэ size
  - entry: theory3, 3 ыкӏи 18
  - entry: theory3, 0 ыкӏи 6
  - тиориэ: theory1, linear, 6 ыкӏи 4
  - тиориэ: theory0, linear, 4 ыкӏи 6
  - theory2 2 тиориэ size
  - theory3 10 тиориэ size
  - theory0 3 тиориэ size
  - тиориэ: theory3, table, 0 ыкӏи 0
Data:
  - 3 18 obs
  - 2 14 obs
  - 0 6 obs
  - 12 54 obs
  - 1 10 obs
Rules: rule тиориэ is lossless iff it predict every observation exactly; rule choose the lossless тиориэ of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless тиориэ сыд?

Candidates:
  - entry: theory3, 1 thiab 10
  - entry: theory3, 2 thiab 14
  - theory: theory2, square, 3 thiab 0
  - entry: theory3, 12 thiab 54
  - theory1 theory size 3
  - entry: theory3, 3 thiab 18
  - entry: theory3, 0 thiab 6
  - theory: theory1, linear, 6 thiab 4
  - theory: theory0, linear, 4 thiab 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, rooj, 0 thiab 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Cai: cai theory is lossless iff nws predict every observation exactly; cai choose lossless theory of least size.
Lub ntsiab: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; rooj form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory3, 1 10
  - entry: theory3, 2 14
  - theory: theory2, square, 3 0
  - entry: theory3, 12 54
  - theory1 theory size 3
  - entry: theory3, 3 18
  - entry: theory3, 0 6
  - theory: theory1, linear, 6 4
  - theory: theory0, linear, 4 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, table, 0 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of wy krook size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory ining-jak?

Candidates:
  - entry: theory3, 1 micha' 10
  - entry: theory3, 2 micha' 14
  - theory: theory2, square, 3 micha' 0
  - entry: theory3, 12 micha' 54
  - theory1 theory size 3
  - entry: theory3, 3 micha' 18
  - entry: theory3, 0 micha' 6
  - theory: theory1, linear, 6 micha' 4
  - theory: theory0, linear, 4 micha' 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, table, 0 micha' 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory nanta?

Candidates:
  - entry: theory3, 1 カ 10
  - entry: theory3, 2 カ 14
  - theory: theory2, square, 3 カ 0
  - entry: theory3, 12 カ 54
  - theory1 3 theory size
  - entry: theory3, 3 カ 18
  - entry: theory3, 0 カ 6
  - theory: theory1, linear, 6 カ 4
  - theory: theory0, linear, 4 カ 6
  - theory2 2 theory size
  - theory3 10 theory size
  - theory0 3 theory size
  - theory: theory3, table, 0 カ 0
Data:
  - 3 18 obs
  - 2 14 obs
  - 0 6 obs
  - 12 54 obs
  - 1 10 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 ノカ; square y = x * x + p2 ノカ; constant y = p2 ノカ; table y = entry(x) ノカ.
Smallest lossless theory what?

Candidates:
  - entry: theory3, 1 ынкъам 10
  - entry: theory3, 2 ынкъам 14
  - theory: theory2, square, 3 ынкъам 0
  - entry: theory3, 12 ынкъам 54
  - theory1 theory size 3
  - entry: theory3, 3 ынкъам 18
  - entry: theory3, 0 ынкъам 6
  - theory: theory1, linear, 6 ынкъам 4
  - theory: theory0, linear, 4 ынкъам 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, table, 0 ынкъам 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory3, 1 yéetel 10
  - entry: theory3, 2 yéetel 14
  - theory: theory2, square, 3 yéetel 0
  - entry: theory3, 12 yéetel 54
  - theory1 theory size 3
  - entry: theory3, 3 yéetel 18
  - entry: theory3, 0 yéetel 6
  - theory: theory1, linear, 6 yéetel 4
  - theory: theory0, linear, 4 yéetel 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, table, 0 yéetel 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Rules:
  - rule theory yan lossless iff it predict every observation exactly
  - rule yéey lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory3, 1 10
  - entry: theory3, 2 14
  - theory: theory2, square, 3 0
  - entry: theory3, 12 54
  - theory1 theory size 3
  - entry: theory3, 3 18
  - entry: theory3, 0 6
  - theory: theory1, linear, 6 4
  - theory: theory0, linear, 4 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, mę́soną, 0 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Rules:
  - rule theory is lossless iff ą́wąną predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mę́soną form y = entry(x).
Smallest lossless theory híli?

Candidates:
  - entry: theory3, 1 na 10
  - entry: theory3, 2 na 14
  - theory: theory2, square, 3 na 0
  - entry: theory3, 12 na 54
  - theory1 3 theory size
  - entry: theory3, 3 na 18
  - entry: theory3, 0 na 6
  - theory: theory1, linear, 6 na 4
  - theory: theory0, linear, 4 na 6
  - theory2 2 theory size
  - theory3 10 theory size
  - theory0 3 theory size
  - theory: theory3, table, 0 na 0
Data:
  - 3 18 obs
  - 2 14 obs
  - 0 6 obs
  - 12 54 obs
  - 1 10 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory3, 1 10
  - entry: theory3, 2 14
  - theory: theory2, square, 3 0
  - entry: theory3, 12 54
  - theory1 theory size 3
  - entry: theory3, 3 18
  - entry: theory3, 0 6
  - theory: theory1, linear, 6 4
  - theory: theory0, linear, 4 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, table, 0 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory3, 1 10
  - entry: theory3, 2 14
  - theory: theory2, square, 3 0
  - entry: theory3, 12 54
  - theory1 3 theory size
  - entry: theory3, 3 18
  - entry: theory3, 0 6
  - theory: theory1, linear, 6 4
  - theory: theory0, linear, 4 6
  - theory2 2 theory size
  - theory3 10 theory size
  - theory0 3 theory size
  - theory: theory3, table, 0 0
Data:
  - 3 18 obs
  - 2 14 obs
  - 0 6 obs
  - 12 54 obs
  - 1 10 obs
Rules:
  - rule maya theory is lossless iff it predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory3, 1 ǂʻá 10
  - entry: theory3, 2 ǂʻá 14
  - theory: theory2, square, 3 ǂʻá 0
  - entry: theory3, 12 ǂʻá 54
  - theory1 theory ʻǁnàhã 3
  - entry: theory3, 3 ǂʻá 18
  - entry: theory3, 0 ǂʻá 6
  - theory: theory1, linear, 6 ǂʻá 4
  - theory: theory0, linear, 4 ǂʻá 6
  - theory2 theory ʻǁnàhã 2
  - theory3 theory ʻǁnàhã 10
  - theory0 theory ʻǁnàhã 3
  - theory: theory3, table, 0 ǂʻá 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Rules:
  - rule theory ǀîi lossless iff èh predict every observation exactly
  - rule choose lossless theory of least ʻǁnàhã
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory3, 1 10
  - entry: theory3, 2 14
  - theory: theory2, square, 3 0
  - entry: theory3, 12 54
  - theory1 3 theory size
  - entry: theory3, 3 18
  - entry: theory3, 0 6
  - theory: theory1, linear, 6 4
  - theory: theory0, linear, 4 6
  - theory2 2 theory size
  - theory3 10 theory size
  - theory0 3 theory size
  - theory: theory3, остол, 0 0
Data:
  - 3 18 obs
  - 2 14 obs
  - 0 6 obs
  - 12 54 obs
  - 1 10 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; остол y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory3, 1 10
  - entry: theory3, 2 14
  - theory: theory2, square, 3 0
  - entry: theory3, 12 54
  - theory1 theory size 3
  - entry: theory3, 3 18
  - entry: theory3, 0 6
  - theory: theory1, linear, 6 4
  - theory: theory0, linear, 4 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, table, 0 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory3, 1 10
  - entry: theory3, 2 14
  - theory: theory2, square, 3 0
  - entry: theory3, 12 54
  - theory1 3 theory size
  - entry: theory3, 3 18
  - entry: theory3, 0 6
  - theory: theory1, linear, 6 4
  - theory: theory0, linear, 4 6
  - theory2 2 theory size
  - theory3 10 theory size
  - theory0 3 theory size
  - theory: theory3, table, 0 0
Data:
  - 3 18 obs
  - 2 14 obs
  - 0 6 obs
  - 12 54 obs
  - 1 10 obs
Rules:
  - rule theory is lossless iff kitu predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory3, 1 10
  - entry: theory3, 2 14
  - theory: theory2, square, 3 0
  - entry: theory3, 12 54
  - theory1 theory size 3
  - entry: theory3, 3 18
  - entry: theory3, 0 6
  - theory: theory1, linear, 6 4
  - theory: theory0, linear, 4 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, mesa, 0 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mesa form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory3, 1 10
  - entry: theory3, 2 14
  - theory: theory2, square, 3 0
  - entry: theory3, 12 54
  - theory1 theory size 3
  - entry: theory3, 3 18
  - entry: theory3, 0 6
  - theory: theory1, linear, 6 4
  - theory: theory0, linear, 4 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, table, 0 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Rules:
  - rule theory nemi lossless iff yaja predict every observation exactly
  - rule choose ne lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ne table form y = entry(x).
Smallest lossless theory tay?

Les candidats sont:
  - article: theory3, 1 et 10
  - article: theory3, 2 et 14
  - théorie: theory2, square, 3 et 0
  - article: theory3, 12 et 54
  - theory1 théorie taille 3
  - article: theory3, 3 et 18
  - article: theory3, 0 et 6
  - théorie: theory1, linear, 6 et 4
  - théorie: theory0, linear, 4 et 6
  - theory2 théorie taille 2
  - theory3 théorie taille 10
  - theory0 théorie taille 3
  - théorie: theory3, table, 0 et 0
Les données sont:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Les règles sont:
  - règle un théorie être lossless ssi il prédire tout observation exactement
  - règle choisir le lossless théorie du moindre taille
La sémantique est : linear former y = p1 * x + p2 ; square former y = x * x + p2 ; constant former y = p2 ; la table former y = entry(x).
Quoi smallest lossless théorie ?

Kandidato:
  - entry: theory3, 1 kaj 10
  - entry: theory3, 2 kaj 14
  - teorio: theory2, square, 3 kaj 0
  - entry: theory3, 12 kaj 54
  - theory1 teorio grandeco 3
  - entry: theory3, 3 kaj 18
  - entry: theory3, 0 kaj 6
  - teorio: theory1, linear, 6 kaj 4
  - teorio: theory0, linear, 4 kaj 6
  - theory2 teorio grandeco 2
  - theory3 teorio grandeco 10
  - theory0 teorio grandeco 3
  - teorio: theory3, tablo, 0 kaj 0
Datumo:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Regulo: regulo teorio egali lossless iff ĝi predict ĉiu observo ekzakte; regulo elekti lossless teorio de plej malmulta grandeco.
Semantics: linear formi y = p1 * x + p2; square formi y = x * x + p2; constant formi y = p2; tablo formi y = entry(x).
Smallest lossless teorio kio?

Indulók:
  - szócikk: theory3, 1 és 10
  - szócikk: theory3, 2 és 14
  - elmélet: theory2, square, 3 és 0
  - szócikk: theory3, 12 és 54
  - theory1 elmélet méret 3
  - szócikk: theory3, 3 és 18
  - szócikk: theory3, 0 és 6
  - elmélet: theory1, linear, 6 és 4
  - elmélet: theory0, linear, 4 és 6
  - theory2 elmélet méret 2
  - theory3 elmélet méret 10
  - theory0 elmélet méret 3
  - elmélet: theory3, asztal, 0 és 0
Adat:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Szabályok:
  - szabály elmélet van veszteségmentes acsa az megjósol minden megfigyelés pontosan
  - szabály kiválaszt a veszteségmentes elmélet of legkisebb méret
Szemantika: linear kialakít y = p1 * x + p2; square kialakít y = x * x + p2; constant kialakít y = p2; a asztal kialakít y = entry(x).
Smallest veszteségmentes elmélet melyik?

候選人:
  - entry:theory3, 1及10
  - entry:theory3, 2及14
  - theory:theory2, square, 3及0
  - entry:theory3, 12及54
  - theory1theory size3
  - entry:theory3, 3及18
  - entry:theory3, 0及6
  - theory:theory1, linear, 6及4
  - theory:theory0, linear, 4及6
  - theory2theory size2
  - theory3theory size10
  - theory0theory size3
  - theory:theory3, 檯, 0及0
數據:
  - 3obs18
  - 2obs14
  - 0obs6
  - 12obs54
  - 1obs10
rules:rule:一theory是losslessiffitpredict每observationexactly; rule:揀losslesstheory...嘅leastsize.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; 檯formy = entry(x).
smallest lossless theory乜嘢?

Candidates:
  - entry: theory3, 1 とぅ 10
  - entry: theory3, 2 とぅ 14
  - theory: theory2, square, 3 とぅ 0
  - entry: theory3, 12 とぅ 54
  - theory1 theory size 3
  - entry: theory3, 3 とぅ 18
  - entry: theory3, 0 とぅ 6
  - theory: theory1, linear, 6 とぅ 4
  - theory: theory0, linear, 4 とぅ 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, table, 0 とぅ 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Rules: rule theory 有ん lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Үміткер:
  - entry: theory3, 1 және 10
  - entry: theory3, 2 және 14
  - теория: theory2, square, 3 және 0
  - entry: theory3, 12 және 54
  - theory1 теория мөлшер 3
  - entry: theory3, 3 және 18
  - entry: theory3, 0 және 6
  - теория: theory1, linear, 6 және 4
  - теория: theory0, linear, 4 және 6
  - theory2 теория мөлшер 2
  - theory3 теория мөлшер 10
  - theory0 теория мөлшер 3
  - теория: theory3, үстел, 0 және 0
Деректер:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Ереже: ереже теория is lossless iff ол predict әр бақылау exactly; ереже таңдау lossless теория туралы least мөлшер.
Семантикалық: linear пішін y = p1 * x + p2; square пішін y = x * x + p2; constant пішін y = p2; үстел пішін y = entry(x).
Smallest lossless теория не?

מועמדת:
  - entry: theory3, 1 וְ־ 10
  - entry: theory3, 2 וְ־ 14
  - תּוֹרָה: theory2, square, 3 וְ־ 0
  - entry: theory3, 12 וְ־ 54
  - theory1 תּוֹרָה גֹּדֶל 3
  - entry: theory3, 3 וְ־ 18
  - entry: theory3, 0 וְ־ 6
  - תּוֹרָה: theory1, linear, 6 וְ־ 4
  - תּוֹרָה: theory0, linear, 4 וְ־ 6
  - theory2 תּוֹרָה גֹּדֶל 2
  - theory3 תּוֹרָה גֹּדֶל 10
  - theory0 תּוֹרָה גֹּדֶל 3
  - תּוֹרָה: theory3, טַבְלָה, 0 וְ־ 0
נְתוּנִים:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
מָשַׁל:
  - מָשַׁל אַחַת תּוֹרָה הוא lossless אםם זֶה predict כֹּל תַּצְפִּית בדיוק
  - מָשַׁל בחר ה־ lossless תּוֹרָה שֶׁל least גֹּדֶל
תורת המשמעים: linear צורה y = p1 * x + p2; square צורה y = x * x + p2; constant צורה y = p2; טַבְלָה ה־ צורה y = entry(x).
איזה smallest lossless תּוֹרָה?

Candidates:
  - entry: theory3, 1 დო 10
  - entry: theory3, 2 დო 14
  - theory: theory2, square, 3 დო 0
  - entry: theory3, 12 დო 54
  - theory1 theory size 3
  - entry: theory3, 3 დო 18
  - entry: theory3, 0 დო 6
  - theory: theory1, linear, 6 დო 4
  - theory: theory0, linear, 4 დო 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, table, 0 დო 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Kandidat:
  - lema: theory3, 1 dan 10
  - lema: theory3, 2 dan 14
  - teori: theory2, square, 3 dan 0
  - lema: theory3, 12 dan 54
  - theory1 teori ukuran 3
  - lema: theory3, 3 dan 18
  - lema: theory3, 0 dan 6
  - teori: theory1, linear, 6 dan 4
  - teori: theory0, linear, 4 dan 6
  - theory2 teori ukuran 2
  - theory3 teori ukuran 10
  - theory0 teori ukuran 3
  - teori: theory3, meja, 0 dan 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Rules:
  - rule teori berada lossless iff it predict setiap observation tepat
  - rule memilih si lossless teori dari least ukuran
Semantik: linear formulir y = p1 * x + p2; square formulir y = x * x + p2; constant formulir y = p2; meja si formulir y = entry(x).
Smallest lossless teori apa?

បេក្ខជន:
  - មេពាក្យ:theory3, 1នឹង10
  - មេពាក្យ:theory3, 2នឹង14
  - ទ្រឹស្ដី:theory2, square, 3នឹង0
  - មេពាក្យ:theory3, 12នឹង54
  - theory1ទ្រឹស្ដីទំហំ3
  - មេពាក្យ:theory3, 3នឹង18
  - មេពាក្យ:theory3, 0នឹង6
  - ទ្រឹស្ដី:theory1, linear, 6នឹង4
  - ទ្រឹស្ដី:theory0, linear, 4នឹង6
  - theory2ទ្រឹស្ដីទំហំ2
  - theory3ទ្រឹស្ដីទំហំ10
  - theory0ទ្រឹស្ដីទំហំ3
  - ទ្រឹស្ដី:theory3, តុ, 0នឹង0
ទិន្នន័យ:
  - 3obs18
  - 2obs14
  - 0obs6
  - 12obs54
  - 1obs10
ក្បួន:ក្បួន:ទ្រឹស្ដីត្រូវបានlosslessiffវាចាប់យាមរាល់គំនន់exactly; ក្បួន:រើសthelosslessទ្រឹស្ដីនៃleastទំហំ.
និឃណ្ដសាស្ត្រ:linearគ្រោងy = p1 * x + p2; squareគ្រោងy = x * x + p2; constantគ្រោងy = p2; តុគ្រោងy = entry(x).
smallestlosslessទ្រឹស្ដីអី?

ຜູ້ສະໝັກ:
  - entry:theory3, 1ແລະ10
  - entry:theory3, 2ແລະ14
  - ທິດສະດີ:theory2, square, 3ແລະ0
  - entry:theory3, 12ແລະ54
  - theory1ທິດສະດີຂະຫນາດ3
  - entry:theory3, 3ແລະ18
  - entry:theory3, 0ແລະ6
  - ທິດສະດີ:theory1, linear, 6ແລະ4
  - ທິດສະດີ:theory0, linear, 4ແລະ6
  - theory2ທິດສະດີຂະຫນາດ2
  - theory3ທິດສະດີຂະຫນາດ10
  - theory0ທິດສະດີຂະຫນາດ3
  - ທິດສະດີ:theory3, ໂຕະ, 0ແລະ0
ຂໍ້ມູນ:
  - 3obs18
  - 2obs14
  - 0obs6
  - 12obs54
  - 1obs10
ກະຕິກາ:ກະຕິກາ:ທິດສະດີຢູ່losslessiffມັນທຳນວາຍທຸກobservationexactly; ກະຕິກາ:ເລືອກlosslessທິດສະດີຂອງleastຂະຫນາດ.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; ໂຕະformy = entry(x).
smallestlosslessທິດສະດີຫຍັງ?

candidates:
  - entry: theory3, 1 మరియు 10
  - entry: theory3, 2 మరియు 14
  - theory: theory2, square, 3 మరియు 0
  - entry: theory3, 12 మరియు 54
  - theory1 3 theory size
  - entry: theory3, 3 మరియు 18
  - entry: theory3, 0 మరియు 6
  - theory: theory1, linear, 6 మరియు 4
  - theory: theory0, linear, 4 మరియు 6
  - theory2 2 theory size
  - theory3 10 theory size
  - theory0 3 theory size
  - theory: theory3, బల్ల, 0 మరియు 0
data:
  - 3 18 obs
  - 2 14 obs
  - 0 6 obs
  - 12 54 obs
  - 1 10 obs
నియమం: నియమం theory ఉండు lossless iff it predict ప్రతి పరిశీలన exactly; నియమం choose lossless theory of least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; బల్ల y = entry(x) form.
smallest lossless theory ఏమిటి?

Candidates:
  - entry: theory3, 1 10
  - entry: theory3, 2 14
  - theory: theory2, square, 3 0
  - entry: theory3, 12 54
  - theory1 theory size 3
  - entry: theory3, 3 18
  - entry: theory3, 0 6
  - theory: theory1, linear, 6 4
  - theory: theory0, linear, 4 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, table, 0 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Rules: rule theory wà lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
What smallest lossless theory?

Candidates:
  - entry: theory3, 1 10
  - entry: theory3, 2 14
  - theory: theory2, square, 3 0
  - entry: theory3, 12 54
  - theory1 3 theory size
  - entry: theory3, 3 18
  - entry: theory3, 0 6
  - theory: theory1, linear, 6 4
  - theory: theory0, linear, 4 6
  - theory2 2 theory size
  - theory3 10 theory size
  - theory0 3 theory size
  - theory: theory3, table, 0 0
Data:
  - 3 18 obs
  - 2 14 obs
  - 0 6 obs
  - 12 54 obs
  - 1 10 obs
Rules:
  - rule theory naiágúóli lossless iff it predict every observation exactly
  - rule choose the lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

candidates:
  - entry: theory3, 1 10
  - entry: theory3, 2 14
  - theory: theory2, square, 3 0
  - entry: theory3, 12 54
  - theory1 theory size 3
  - entry: theory3, 3 18
  - entry: theory3, 0 6
  - theory: theory1, linear, 6 4
  - theory: theory0, linear, 4 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, table, 0 0
data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
smallest lossless theory what?

Candidates:
  - entry: theory3, 1 10
  - entry: theory3, 2 14
  - theory: theory2, square, 3 0
  - entry: theory3, 12 54
  - theory1 theory size 3
  - entry: theory3, 3 18
  - entry: theory3, 0 6
  - theory: theory1, linear, 6 4
  - theory: theory0, linear, 4 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, tafra, 0 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; tafra form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory3, 1 10
  - entry: theory3, 2 14
  - theory: theory2, square, 3 0
  - entry: theory3, 12 54
  - theory1 theory size 3
  - entry: theory3, 3 18
  - entry: theory3, 0 6
  - theory: theory1, linear, 6 4
  - theory: theory0, linear, 4 6
  - theory2 theory size 2
  - theory3 theory size 10
  - theory0 theory size 3
  - theory: theory3, táxemésėhestȯtse, 0 0
Data:
  - 3 obs 18
  - 2 obs 14
  - 0 obs 6
  - 12 obs 54
  - 1 obs 10
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; táxemésėhestȯtse form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory3, 1 10
  - entry: theory3, 2 14
  - theory: theory2, square, 3 0
  - entry: theory3, 12 54
  - theory1 3 theory size
  - entry: theory3, 3 18
  - entry: theory3, 0 6
  - theory: theory1, linear, 6 4
  - theory: theory0, linear, 4 6
  - theory2 2 theory size
  - theory3 10 theory size
  - theory0 3 theory size
  - theory: theory3, ствал, 0 0
Data:
  - 3 18 obs
  - 2 14 obs
  - 0 6 obs
  - 12 54 obs
  - 1 10 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; ствал y = entry(x) form.
Smallest lossless theory вуч?

The candidates are:
  - entry: theory0, 4 and 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 and 126
  - entry: theory0, 2 and 9
  - theory: theory0, table, 0 and 0
  - theory: theory2, square, 4 and 7
  - entry: theory0, 0 and 5
  - theory3 theory size 2
  - theory: theory3, square, 6 and 5
  - theory1 theory size 3
  - entry: theory0, 5 and 30
  - theory: theory1, linear, 6 and 8
The data are:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

Los candidatos son:
  - la entrada: theory0, 4 y 21
  - theory2 el tamaño de la teoría 2
  - theory0 el tamaño de la teoría 10
  - la entrada: theory0, 11 y 126
  - la entrada: theory0, 2 y 9
  - la teoría: theory0, mesa, 0 y 0
  - la teoría: theory2, square, 4 y 7
  - la entrada: theory0, 0 y 5
  - theory3 el tamaño de la teoría 2
  - la teoría: theory3, square, 6 y 5
  - theory1 el tamaño de la teoría 3
  - la entrada: theory0, 5 y 30
  - la teoría: theory1, linear, 6 y 8
Los datos son:
  - 4 la observación 21
  - 5 la observación 30
  - 11 la observación 126
  - 0 la observación 5
  - 2 la observación 9
Las reglas son:
  - la regla: a la teoría es lossless si y sólo si it predice every observation exactamente
  - la regla: choose el lossless la teoría de least tamaño
La semántica es: linear la forma y = p1 * x + p2; square la forma y = x * x + p2; constant la forma y = p2; la mesa la forma y = entry(x).
¿Qué smallest lossless la teoría?

候选项如下：
  - 的条目是：theory0、4和21
  - theory2的理论规模是2
  - theory0的理论规模是10
  - 的条目是：theory0、11和126
  - 的条目是：theory0、2和9
  - 的理论是：theory0、桌子、0和0
  - 的理论是：theory2、square、4和7
  - 的条目是：theory0、0和5
  - theory3的理论规模是2
  - 的理论是：theory3、square、6和5
  - theory1的理论规模是3
  - 的条目是：theory0、5和30
  - 的理论是：theory1、linear、6和8
数据如下：
  - 4观察到21
  - 5观察到30
  - 11观察到126
  - 0观察到5
  - 2观察到9
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

Adaylar:
  - entry: theory0, 4 ve 21
  - theory2 2 kuram boyut
  - theory0 10 kuram boyut
  - entry: theory0, 11 ve 126
  - entry: theory0, 2 ve 9
  - kuram: theory0, masa, 0 ve 0
  - kuram: theory2, square, 4 ve 7
  - entry: theory0, 0 ve 5
  - theory3 2 kuram boyut
  - kuram: theory3, square, 6 ve 5
  - theory1 3 kuram boyut
  - entry: theory0, 5 ve 30
  - kuram: theory1, linear, 6 ve 8
Veriler:
  - 4 21 obs
  - 5 30 obs
  - 11 126 obs
  - 0 5 obs
  - 2 9 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

Wagombea ni:
  - entry: theory0, 4 na 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 na 126
  - entry: theory0, 2 na 9
  - theory: theory0, meza, 0 na 0
  - theory: theory2, square, 4 na 7
  - entry: theory0, 0 na 5
  - theory3 theory size 2
  - theory: theory3, square, 6 na 5
  - theory1 theory size 3
  - entry: theory0, 5 na 30
  - theory: theory1, linear, 6 na 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

The candidates are:
  - entry: theory0, 4 and 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 and 126
  - entry: theory0, 2 and 9
  - theory: theory0, table, 0 and 0
  - theory: theory2, square, 4 and 7
  - entry: theory0, 0 and 5
  - theory3 theory size 2
  - theory: theory3, square, 6 and 5
  - theory1 theory size 3
  - entry: theory0, 5 and 30
  - theory: theory1, linear, 6 and 8
The data are:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

{candidates: [(entry theory0 4 21) (theory_size theory2 2) (theory_size theory0 10) (entry theory0 11 126) (entry theory0 2 9) (theory theory0 table 0 0) (theory theory2 square 4 7) (entry theory0 0 5) (theory_size theory3 2) (theory theory3 square 6 5) (theory_size theory1 3) (entry theory0 5 30) (theory theory1 linear 6 8)], data: [(obs 4 21) (obs 5 30) (obs 11 126) (obs 0 5) (obs 2 9)], query: smallest_lossless_theory, rules: [(rule (a_theory_is_lossless_iff_it_predicts_every_observation_exactly)) (rule (choose_the_lossless_theory_of_least_size))], semantics: [(form linear "y = p1 * x + p2") (form square "y = x * x + p2") (form constant "y = p2") (form table "y = entry(x)")]}

Die Kandidaten sind:
  - Eintrag: theory0, 4 und 21
  - theory2 Theorie Größe 2
  - theory0 Theorie Größe 10
  - Eintrag: theory0, 11 und 126
  - Eintrag: theory0, 2 und 9
  - Theorie: theory0, Tisch, 0 und 0
  - Theorie: theory2, square, 4 und 7
  - Eintrag: theory0, 0 und 5
  - theory3 Theorie Größe 2
  - Theorie: theory3, square, 6 und 5
  - theory1 Theorie Größe 3
  - Eintrag: theory0, 5 und 30
  - Theorie: theory1, linear, 6 und 8
Die Daten sind:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Die Regeln sind:
  - Regel ein Theorie werden verlustfrei gdw. er vorhersagen jeder Beobachtung genau
  - Regel wählen der verlustfrei Theorie aus geringst Größe
Die Semantik ist: linear formen y = p1 * x + p2; square formen y = x * x + p2; constant formen y = p2; der Tisch formen y = entry(x).
Was smallest verlustfrei Theorie?

Кандѝда̄т:
  - одредница: theory0, 4 и 21
  - theory2 тѐо̄рија величѝна 2
  - theory0 тѐо̄рија величѝна 10
  - одредница: theory0, 11 и 126
  - одредница: theory0, 2 и 9
  - тѐо̄рија: theory0, сто̑л, 0 и 0
  - тѐо̄рија: theory2, square, 4 и 7
  - одредница: theory0, 0 и 5
  - theory3 тѐо̄рија величѝна 2
  - тѐо̄рија: theory3, square, 6 и 5
  - theory1 тѐо̄рија величѝна 3
  - одредница: theory0, 5 и 30
  - тѐо̄рија: theory1, linear, 6 и 8
Податци:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Пра̏вило:
  - пра̏вило тѐо̄рија би̏ти lossless iff оно predvidjeti сва̏кӣ опа́жа̄ње тачно
  - пра̏вило изабрати lossless тѐо̄рија od minimalan величѝна
Сема̀нтика: linear oblik y = p1 * x + p2; square oblik y = x * x + p2; constant oblik y = p2; сто̑л oblik y = entry(x).
Smallest lossless тѐо̄рија kakav?

Ehdokkaat:
  - artikkeli: theory0, 4 ja 21
  - theory2 teoria koko 2
  - theory0 teoria koko 10
  - artikkeli: theory0, 11 ja 126
  - artikkeli: theory0, 2 ja 9
  - teoria: theory0, pöytä, 0 ja 0
  - teoria: theory2, square, 4 ja 7
  - artikkeli: theory0, 0 ja 5
  - theory3 teoria koko 2
  - teoria: theory3, square, 6 ja 5
  - theory1 teoria koko 3
  - artikkeli: theory0, 5 ja 30
  - teoria: theory1, linear, 6 ja 8
Tieto:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Säännöt:
  - sääntö teoria tulla häviötön joss se ennakoida jokainen havainnointi täsmälleen
  - sääntö valita häviötön teoria vaille vähin koko
Semantiikka: linear muotoilla y = p1 * x + p2; square muotoilla y = x * x + p2; constant muotoilla y = p2; pöytä muotoilla y = entry(x).
Mikä smallest häviötön teoria?

候选项如下：
  - 的条目是：theory0、4和21
  - theory2的理论规模是2
  - theory0的理论规模是10
  - 的条目是：theory0、11和126
  - 的条目是：theory0、2和9
  - 的理论是：theory0、桌子、0和0
  - 的理论是：theory2、square、4和7
  - 的条目是：theory0、0和5
  - theory3的理论规模是2
  - 的理论是：theory3、square、6和5
  - theory1的理论规模是3
  - 的条目是：theory0、5和30
  - 的理论是：theory1、linear、6和8
数据如下：
  - 4观察到21
  - 5观察到30
  - 11观察到126
  - 0观察到5
  - 2观察到9
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

候補者:
  - 項目:theory0, 4と21
  - theory22理論大きさ
  - theory010理論大きさ
  - 項目:theory0, 11と126
  - 項目:theory0, 2と9
  - 理論:theory0, 台, 0と0
  - 理論:theory2, square, 4と7
  - 項目:theory0, 0と5
  - theory32理論大きさ
  - 理論:theory3, square, 6と5
  - theory13理論大きさ
  - 項目:theory0, 5と30
  - 理論:theory1, linear, 6と8
資料:
  - 421obs
  - 530obs
  - 11126obs
  - 05obs
  - 29obs
規則:規則:理論れるロスレスiffこれ予言する凡ゆる観察正確に; 規則:選ぶロスレス理論の中の最小の大きさ.
意味論:lineary = p1 * x + p2形作る; squarey = x * x + p2形作る; constanty = p2形作る; 台y = entry(x)形作る.
smallestロスレス理論何と?

Adaylar:
  - entry: theory0, 4 ve 21
  - theory2 2 kuram boyut
  - theory0 10 kuram boyut
  - entry: theory0, 11 ve 126
  - entry: theory0, 2 ve 9
  - kuram: theory0, masa, 0 ve 0
  - kuram: theory2, square, 4 ve 7
  - entry: theory0, 0 ve 5
  - theory3 2 kuram boyut
  - kuram: theory3, square, 6 ve 5
  - theory1 3 kuram boyut
  - entry: theory0, 5 ve 30
  - kuram: theory1, linear, 6 ve 8
Veriler:
  - 4 21 obs
  - 5 30 obs
  - 11 126 obs
  - 0 5 obs
  - 2 9 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

مُرَشَّح:
  - مَدْخَل: theory0، 4 وَـ 21
  - نَظَرِيَّة مَقَاس theory2 2
  - نَظَرِيَّة مَقَاس theory0 10
  - مَدْخَل: theory0، 11 وَـ 126
  - مَدْخَل: theory0، 2 وَـ 9
  - نَظَرِيَّة: theory0، طَاوِلَة، 0 وَـ 0
  - نَظَرِيَّة: theory2، square، 4 وَـ 7
  - مَدْخَل: theory0، 0 وَـ 5
  - نَظَرِيَّة مَقَاس theory3 2
  - نَظَرِيَّة: theory3، square، 6 وَـ 5
  - نَظَرِيَّة مَقَاس theory1 3
  - مَدْخَل: theory0، 5 وَـ 30
  - نَظَرِيَّة: theory1، linear، 6 وَـ 8
بَيَانَات:
  - obs 4 21
  - obs 5 30
  - obs 11 126
  - obs 0 5
  - obs 2 9
قَانُون:
  - قَانُون نَظَرِيَّة كَانَ lossless iff هُوَ تَنَبَّأَ كُلّ رَصْد بِالضَّبْط
  - قَانُون اِخْتَارَ الـ lossless نَظَرِيَّة مِنْ أَقَلَّ مَقَاس
عِلْم اَلْمَعَانِي: شَكَّلَ linear y = p1 * x + p2؛ شَكَّلَ square y = x * x + p2؛ شَكَّلَ constant y = p2؛ شَكَّلَ الـ طَاوِلَة y = entry(x).
smallest lossless نَظَرِيَّة مَاذَا؟

Კანდიდატები:
  - სასათაურო სიტყვა: theory0, 4 და 21
  - theory2 2 თეორია ზომა
  - theory0 10 თეორია ზომა
  - სასათაურო სიტყვა: theory0, 11 და 126
  - სასათაურო სიტყვა: theory0, 2 და 9
  - თეორია: theory0, მაგიდა, 0 და 0
  - თეორია: theory2, square, 4 და 7
  - სასათაურო სიტყვა: theory0, 0 და 5
  - theory3 2 თეორია ზომა
  - თეორია: theory3, square, 6 და 5
  - theory1 3 თეორია ზომა
  - სასათაურო სიტყვა: theory0, 5 და 30
  - თეორია: theory1, linear, 6 და 8
Მონაცემები:
  - 4 21 obs
  - 5 30 obs
  - 11 126 obs
  - 0 5 obs
  - 2 9 obs
Წესი:
  - წესი თეორია ყოფნა უდანაკარგო iff ის predict ყველა დაკვირვება ზუსტად
  - წესი ამორჩევა უდანაკარგო თეორია of least ზომა
Სემანტიკა: linear y = p1 * x + p2 ბლანკი; square y = x * x + p2 ბლანკი; constant y = p2 ბლანკი; მაგიდა y = entry(x) ბლანკი.
Smallest უდანაკარგო თეორია რა?

Kaiwhakauru:
  - tāurunga: theory0, 4 me 21
  - ariā size theory2 2
  - ariā size theory0 10
  - tāurunga: theory0, 11 me 126
  - tāurunga: theory0, 2 me 9
  - ariā: theory0, tēpu, 0 me 0
  - ariā: theory2, square, 4 me 7
  - tāurunga: theory0, 0 me 5
  - ariā size theory3 2
  - ariā: theory3, square, 6 me 5
  - ariā size theory1 3
  - tāurunga: theory0, 5 me 30
  - ariā: theory1, linear, 6 me 8
Hōtuku:
  - obs 4 21
  - obs 5 30
  - obs 11 126
  - obs 0 5
  - obs 2 9
Rekureihana:
  - rekureihana ariā is lossless iff it matakite every observation pū
  - rekureihana whiri te lossless ariā o least size
Semantics: āhua linear y = p1 * x + p2; āhua square y = x * x + p2; āhua constant y = p2; āhua te tēpu y = entry(x).
Smallest lossless ariā unutai?

Candidates:
  - mục từ: theory0, 4 và 21
  - theory2 lý thuyết kích thước 2
  - theory0 lý thuyết kích thước 10
  - mục từ: theory0, 11 và 126
  - mục từ: theory0, 2 và 9
  - lý thuyết: theory0, bàn, 0 và 0
  - lý thuyết: theory2, square, 4 và 7
  - mục từ: theory0, 0 và 5
  - theory3 lý thuyết kích thước 2
  - lý thuyết: theory3, square, 6 và 5
  - theory1 lý thuyết kích thước 3
  - mục từ: theory0, 5 và 30
  - lý thuyết: theory1, linear, 6 và 8
Dữ liệu:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Quy tắc:
  - quy tắc lý thuyết được lossless iff nó dự báo mỗi observation đúng rồi
  - quy tắc chọn the lossless lý thuyết bằng least kích thước
Ngữ nghĩa: linear làm thành y = p1 * x + p2; square làm thành y = x * x + p2; constant làm thành y = p2; bàn làm thành y = entry(x).
Smallest lossless lý thuyết gì?

ผู้สมัคร:
  - entry:theory0, 4และ21
  - theory2ทฤษฎีขนาด2
  - theory0ทฤษฎีขนาด10
  - entry:theory0, 11และ126
  - entry:theory0, 2และ9
  - ทฤษฎี:theory0, โต๊ะ, 0และ0
  - ทฤษฎี:theory2, square, 4และ7
  - entry:theory0, 0และ5
  - theory3ทฤษฎีขนาด2
  - ทฤษฎี:theory3, square, 6และ5
  - theory1ทฤษฎีขนาด3
  - entry:theory0, 5และ30
  - ทฤษฎี:theory1, linear, 6และ8
ข้อมูล:
  - 4obs21
  - 5obs30
  - 11obs126
  - 0obs5
  - 2obs9
กฎ:กฎ:ทฤษฎีถูกlosslessiffมันทำนายทุกการสังเกตexactly; กฎ:เลือกlosslessทฤษฎีของleastขนาด.
อรรถศาสตร์:linearรูปร่างy = p1 * x + p2; squareรูปร่างy = x * x + p2; constantรูปร่างy = p2; โต๊ะรูปร่างy = entry(x).
smallestlosslessทฤษฎีอะไร?

வேட்பாளர்:
  - உள்நுழைவதற்கு அனுமதி: theory0, 4 மற்றும் 21
  - theory2 2 theory size
  - theory0 10 theory size
  - உள்நுழைவதற்கு அனுமதி: theory0, 11 மற்றும் 126
  - உள்நுழைவதற்கு அனுமதி: theory0, 2 மற்றும் 9
  - theory: theory0, மேசை, 0 மற்றும் 0
  - theory: theory2, square, 4 மற்றும் 7
  - உள்நுழைவதற்கு அனுமதி: theory0, 0 மற்றும் 5
  - theory3 2 theory size
  - theory: theory3, square, 6 மற்றும் 5
  - theory1 3 theory size
  - உள்நுழைவதற்கு அனுமதி: theory0, 5 மற்றும் 30
  - theory: theory1, linear, 6 மற்றும் 8
தரவுகள்:
  - 4 21 obs
  - 5 30 obs
  - 11 126 obs
  - 0 5 obs
  - 2 9 obs
rules: rule theory படு lossless iff it கணி ஒவ்வொரு observation exactly; rule choose lossless theory கொண்ட least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; மேசை y = entry(x) form.
smallest lossless theory என்ன?

Wagombea ni:
  - entry: theory0, 4 na 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 na 126
  - entry: theory0, 2 na 9
  - theory: theory0, meza, 0 na 0
  - theory: theory2, square, 4 na 7
  - entry: theory0, 0 na 5
  - theory3 theory size 2
  - theory: theory3, square, 6 na 5
  - theory1 theory size 3
  - entry: theory0, 5 na 30
  - theory: theory1, linear, 6 na 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

Candidates:
  - entry: theory0, 4 dóó 21
  - theory2 2 theory size
  - theory0 10 theory size
  - entry: theory0, 11 dóó 126
  - entry: theory0, 2 dóó 9
  - theory: theory0, bikááʼ adání, 0 dóó 0
  - theory: theory2, square, 4 dóó 7
  - entry: theory0, 0 dóó 5
  - theory3 2 theory size
  - theory: theory3, square, 6 dóó 5
  - theory1 3 theory size
  - entry: theory0, 5 dóó 30
  - theory: theory1, linear, 6 dóó 8
Data:
  - 4 21 obs
  - 5 30 obs
  - 11 126 obs
  - 0 5 obs
  - 2 9 obs
Bee hazʼáanii:
  - bee hazʼáanii theory átʼé lossless iff it predict every observation exactly
  - bee hazʼáanii choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; bikááʼ adání y = entry(x) form.
Smallest lossless theory haʼátʼíísh?

Candidates:
  - entry: theory0, 4 aamma 21
  - theory2 2 theory size
  - theory0 10 theory size
  - entry: theory0, 11 aamma 126
  - entry: theory0, 2 aamma 9
  - theory: theory0, table, 0 aamma 0
  - theory: theory2, square, 4 aamma 7
  - entry: theory0, 0 aamma 5
  - theory3 2 theory size
  - theory: theory3, square, 6 aamma 5
  - theory1 3 theory size
  - entry: theory0, 5 aamma 30
  - theory: theory1, linear, 6 aamma 8
Data:
  - 4 21 obs
  - 5 30 obs
  - 11 126 obs
  - 0 5 obs
  - 2 9 obs
Rules: rule theory a lossless iff una predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 blanketti; square y = x * x + p2 blanketti; constant y = p2 blanketti; table y = entry(x) blanketti.
Smallest lossless theory what?

Candidates:
  - entry: theory0, 4 na 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 na 126
  - entry: theory0, 2 na 9
  - theory: theory0, table, 0 na 0
  - theory: theory2, square, 4 na 7
  - entry: theory0, 0 na 5
  - theory3 theory size 2
  - theory: theory3, square, 6 na 5
  - theory1 theory size 3
  - entry: theory0, 5 na 30
  - theory: theory1, linear, 6 na 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory bilong least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory0, 4 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 126
  - entry: theory0, 2 9
  - theory: theory0, table, 0 0
  - theory: theory2, square, 4 7
  - entry: theory0, 0 5
  - theory3 theory size 2
  - theory: theory3, square, 6 5
  - theory1 theory size 3
  - entry: theory0, 5 30
  - theory: theory1, linear, 6 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Nikanixi:
  - nikanixi theory is lossless iff it predict every observation exactly
  - nikanixi choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory kwèch?

Candidates:
  - entry: theory0, 4 а 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 а 126
  - entry: theory0, 2 а 9
  - theory: theory0, table, 0 а 0
  - theory: theory2, square, 4 а 7
  - entry: theory0, 0 а 5
  - theory3 theory size 2
  - theory: theory3, square, 6 а 5
  - theory1 theory size 3
  - entry: theory0, 5 а 30
  - theory: theory1, linear, 6 а 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Rules:
  - rule theory хила lossless iff it predict дерриг observation exactly
  - rule хержа lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory фу?

후보자:
  - 항목: theory0, 4 21
  - theory2 2 이론 크기
  - theory0 10 이론 크기
  - 항목: theory0, 11 126
  - 항목: theory0, 2 9
  - 이론: theory0, 테이블, 0 0
  - 이론: theory2, square, 4 7
  - 항목: theory0, 0 5
  - theory3 2 이론 크기
  - 이론: theory3, square, 6 5
  - theory1 3 이론 크기
  - 항목: theory0, 5 30
  - 이론: theory1, linear, 6 8
자료:
  - 4 21 obs
  - 5 30 obs
  - 11 126 obs
  - 0 5 obs
  - 2 9 obs
규칙: 규칙 이론 is lossless iff 이것 예언하다 각 관찰 정확하게; 규칙 고르다 lossless 이론...의 가장 적게 크기.
의미론: linear y = p1 * x + p2 형상; square y = x * x + p2 형상; constant y = p2 형상; 테이블 y = entry(x) 형상.
smallest lossless 이론 무엇?

Kandidatu:
  - sarrera: theory0, 4 eta 21
  - theory2 2 theory tamaina
  - theory0 10 theory tamaina
  - sarrera: theory0, 11 eta 126
  - sarrera: theory0, 2 eta 9
  - theory: theory0, mahai, 0 eta 0
  - theory: theory2, square, 4 eta 7
  - sarrera: theory0, 0 eta 5
  - theory3 2 theory tamaina
  - theory: theory3, square, 6 eta 5
  - theory1 3 theory tamaina
  - sarrera: theory0, 5 eta 30
  - theory: theory1, linear, 6 eta 8
Data:
  - 4 21 obs
  - 5 30 obs
  - 11 126 obs
  - 0 5 obs
  - 2 9 obs
Arau:
  - arau bat theory izan lossless iff it aurresan every observation exactly
  - arau aukeratu the lossless theory of least tamaina
Semantics: linear y = p1 * x + p2 forma; square y = x * x + p2 forma; constant y = p2 forma; mahai y = entry(x) forma.
Smallest lossless theory zer?

ᎠᏙᎩᏯᏍᎩ:
  - entry: theory0, 4 ᎠᎴ 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 ᎠᎴ 126
  - entry: theory0, 2 ᎠᎴ 9
  - theory: theory0, ᎦᏍᎩᎶ, 0 ᎠᎴ 0
  - theory: theory2, square, 4 ᎠᎴ 7
  - entry: theory0, 0 ᎠᎴ 5
  - theory3 theory size 2
  - theory: theory3, square, 6 ᎠᎴ 5
  - theory1 theory size 3
  - entry: theory0, 5 ᎠᎴ 30
  - theory: theory1, linear, 6 ᎠᎴ 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ᎦᏍᎩᎶ form y = entry(x).
What smallest lossless theory?

Candidates:
  - entry: theory0, 4 21
  - theory2 theory chhika 2
  - theory0 theory chhika 10
  - entry: theory0, 11 126
  - entry: theory0, 2 9
  - theory: theory0, patacha, 0 0
  - theory: theory2, square, 4 7
  - entry: theory0, 0 5
  - theory3 theory chhika 2
  - theory: theory3, square, 6 5
  - theory1 theory chhika 3
  - entry: theory0, 5 30
  - theory: theory1, linear, 6 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Rules:
  - rule theory tiyay lossless iff it predict tukuy observation exactly
  - rule akllay lossless theory of least chhika
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; patacha form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory0, 4 ыкӏи 21
  - theory2 2 тиориэ size
  - theory0 10 тиориэ size
  - entry: theory0, 11 ыкӏи 126
  - entry: theory0, 2 ыкӏи 9
  - тиориэ: theory0, table, 0 ыкӏи 0
  - тиориэ: theory2, square, 4 ыкӏи 7
  - entry: theory0, 0 ыкӏи 5
  - theory3 2 тиориэ size
  - тиориэ: theory3, square, 6 ыкӏи 5
  - theory1 3 тиориэ size
  - entry: theory0, 5 ыкӏи 30
  - тиориэ: theory1, linear, 6 ыкӏи 8
Data:
  - 4 21 obs
  - 5 30 obs
  - 11 126 obs
  - 0 5 obs
  - 2 9 obs
Rules: rule тиориэ is lossless iff it predict every observation exactly; rule choose the lossless тиориэ of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless тиориэ сыд?

Candidates:
  - entry: theory0, 4 thiab 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 thiab 126
  - entry: theory0, 2 thiab 9
  - theory: theory0, rooj, 0 thiab 0
  - theory: theory2, square, 4 thiab 7
  - entry: theory0, 0 thiab 5
  - theory3 theory size 2
  - theory: theory3, square, 6 thiab 5
  - theory1 theory size 3
  - entry: theory0, 5 thiab 30
  - theory: theory1, linear, 6 thiab 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Cai: cai theory is lossless iff nws predict every observation exactly; cai choose lossless theory of least size.
Lub ntsiab: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; rooj form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory0, 4 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 126
  - entry: theory0, 2 9
  - theory: theory0, table, 0 0
  - theory: theory2, square, 4 7
  - entry: theory0, 0 5
  - theory3 theory size 2
  - theory: theory3, square, 6 5
  - theory1 theory size 3
  - entry: theory0, 5 30
  - theory: theory1, linear, 6 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of wy krook size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory ining-jak?

Candidates:
  - entry: theory0, 4 micha' 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 micha' 126
  - entry: theory0, 2 micha' 9
  - theory: theory0, table, 0 micha' 0
  - theory: theory2, square, 4 micha' 7
  - entry: theory0, 0 micha' 5
  - theory3 theory size 2
  - theory: theory3, square, 6 micha' 5
  - theory1 theory size 3
  - entry: theory0, 5 micha' 30
  - theory: theory1, linear, 6 micha' 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory nanta?

Candidates:
  - entry: theory0, 4 カ 21
  - theory2 2 theory size
  - theory0 10 theory size
  - entry: theory0, 11 カ 126
  - entry: theory0, 2 カ 9
  - theory: theory0, table, 0 カ 0
  - theory: theory2, square, 4 カ 7
  - entry: theory0, 0 カ 5
  - theory3 2 theory size
  - theory: theory3, square, 6 カ 5
  - theory1 3 theory size
  - entry: theory0, 5 カ 30
  - theory: theory1, linear, 6 カ 8
Data:
  - 4 21 obs
  - 5 30 obs
  - 11 126 obs
  - 0 5 obs
  - 2 9 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 ノカ; square y = x * x + p2 ノカ; constant y = p2 ノカ; table y = entry(x) ノカ.
Smallest lossless theory what?

Candidates:
  - entry: theory0, 4 ынкъам 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 ынкъам 126
  - entry: theory0, 2 ынкъам 9
  - theory: theory0, table, 0 ынкъам 0
  - theory: theory2, square, 4 ынкъам 7
  - entry: theory0, 0 ынкъам 5
  - theory3 theory size 2
  - theory: theory3, square, 6 ынкъам 5
  - theory1 theory size 3
  - entry: theory0, 5 ынкъам 30
  - theory: theory1, linear, 6 ынкъам 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory0, 4 yéetel 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 yéetel 126
  - entry: theory0, 2 yéetel 9
  - theory: theory0, table, 0 yéetel 0
  - theory: theory2, square, 4 yéetel 7
  - entry: theory0, 0 yéetel 5
  - theory3 theory size 2
  - theory: theory3, square, 6 yéetel 5
  - theory1 theory size 3
  - entry: theory0, 5 yéetel 30
  - theory: theory1, linear, 6 yéetel 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Rules:
  - rule theory yan lossless iff it predict every observation exactly
  - rule yéey lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory0, 4 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 126
  - entry: theory0, 2 9
  - theory: theory0, mę́soną, 0 0
  - theory: theory2, square, 4 7
  - entry: theory0, 0 5
  - theory3 theory size 2
  - theory: theory3, square, 6 5
  - theory1 theory size 3
  - entry: theory0, 5 30
  - theory: theory1, linear, 6 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Rules:
  - rule theory is lossless iff ą́wąną predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mę́soną form y = entry(x).
Smallest lossless theory híli?

Candidates:
  - entry: theory0, 4 na 21
  - theory2 2 theory size
  - theory0 10 theory size
  - entry: theory0, 11 na 126
  - entry: theory0, 2 na 9
  - theory: theory0, table, 0 na 0
  - theory: theory2, square, 4 na 7
  - entry: theory0, 0 na 5
  - theory3 2 theory size
  - theory: theory3, square, 6 na 5
  - theory1 3 theory size
  - entry: theory0, 5 na 30
  - theory: theory1, linear, 6 na 8
Data:
  - 4 21 obs
  - 5 30 obs
  - 11 126 obs
  - 0 5 obs
  - 2 9 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory0, 4 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 126
  - entry: theory0, 2 9
  - theory: theory0, table, 0 0
  - theory: theory2, square, 4 7
  - entry: theory0, 0 5
  - theory3 theory size 2
  - theory: theory3, square, 6 5
  - theory1 theory size 3
  - entry: theory0, 5 30
  - theory: theory1, linear, 6 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory0, 4 21
  - theory2 2 theory size
  - theory0 10 theory size
  - entry: theory0, 11 126
  - entry: theory0, 2 9
  - theory: theory0, table, 0 0
  - theory: theory2, square, 4 7
  - entry: theory0, 0 5
  - theory3 2 theory size
  - theory: theory3, square, 6 5
  - theory1 3 theory size
  - entry: theory0, 5 30
  - theory: theory1, linear, 6 8
Data:
  - 4 21 obs
  - 5 30 obs
  - 11 126 obs
  - 0 5 obs
  - 2 9 obs
Rules:
  - rule maya theory is lossless iff it predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory0, 4 ǂʻá 21
  - theory2 theory ʻǁnàhã 2
  - theory0 theory ʻǁnàhã 10
  - entry: theory0, 11 ǂʻá 126
  - entry: theory0, 2 ǂʻá 9
  - theory: theory0, table, 0 ǂʻá 0
  - theory: theory2, square, 4 ǂʻá 7
  - entry: theory0, 0 ǂʻá 5
  - theory3 theory ʻǁnàhã 2
  - theory: theory3, square, 6 ǂʻá 5
  - theory1 theory ʻǁnàhã 3
  - entry: theory0, 5 ǂʻá 30
  - theory: theory1, linear, 6 ǂʻá 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Rules:
  - rule theory ǀîi lossless iff èh predict every observation exactly
  - rule choose lossless theory of least ʻǁnàhã
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory0, 4 21
  - theory2 2 theory size
  - theory0 10 theory size
  - entry: theory0, 11 126
  - entry: theory0, 2 9
  - theory: theory0, остол, 0 0
  - theory: theory2, square, 4 7
  - entry: theory0, 0 5
  - theory3 2 theory size
  - theory: theory3, square, 6 5
  - theory1 3 theory size
  - entry: theory0, 5 30
  - theory: theory1, linear, 6 8
Data:
  - 4 21 obs
  - 5 30 obs
  - 11 126 obs
  - 0 5 obs
  - 2 9 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; остол y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory0, 4 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 126
  - entry: theory0, 2 9
  - theory: theory0, table, 0 0
  - theory: theory2, square, 4 7
  - entry: theory0, 0 5
  - theory3 theory size 2
  - theory: theory3, square, 6 5
  - theory1 theory size 3
  - entry: theory0, 5 30
  - theory: theory1, linear, 6 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory0, 4 21
  - theory2 2 theory size
  - theory0 10 theory size
  - entry: theory0, 11 126
  - entry: theory0, 2 9
  - theory: theory0, table, 0 0
  - theory: theory2, square, 4 7
  - entry: theory0, 0 5
  - theory3 2 theory size
  - theory: theory3, square, 6 5
  - theory1 3 theory size
  - entry: theory0, 5 30
  - theory: theory1, linear, 6 8
Data:
  - 4 21 obs
  - 5 30 obs
  - 11 126 obs
  - 0 5 obs
  - 2 9 obs
Rules:
  - rule theory is lossless iff kitu predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory0, 4 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 126
  - entry: theory0, 2 9
  - theory: theory0, mesa, 0 0
  - theory: theory2, square, 4 7
  - entry: theory0, 0 5
  - theory3 theory size 2
  - theory: theory3, square, 6 5
  - theory1 theory size 3
  - entry: theory0, 5 30
  - theory: theory1, linear, 6 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mesa form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory0, 4 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 126
  - entry: theory0, 2 9
  - theory: theory0, table, 0 0
  - theory: theory2, square, 4 7
  - entry: theory0, 0 5
  - theory3 theory size 2
  - theory: theory3, square, 6 5
  - theory1 theory size 3
  - entry: theory0, 5 30
  - theory: theory1, linear, 6 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Rules:
  - rule theory nemi lossless iff yaja predict every observation exactly
  - rule choose ne lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ne table form y = entry(x).
Smallest lossless theory tay?

Les candidats sont:
  - article: theory0, 4 et 21
  - theory2 théorie taille 2
  - theory0 théorie taille 10
  - article: theory0, 11 et 126
  - article: theory0, 2 et 9
  - théorie: theory0, table, 0 et 0
  - théorie: theory2, square, 4 et 7
  - article: theory0, 0 et 5
  - theory3 théorie taille 2
  - théorie: theory3, square, 6 et 5
  - theory1 théorie taille 3
  - article: theory0, 5 et 30
  - théorie: theory1, linear, 6 et 8
Les données sont:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Les règles sont:
  - règle un théorie être lossless ssi il prédire tout observation exactement
  - règle choisir le lossless théorie du moindre taille
La sémantique est : linear former y = p1 * x + p2 ; square former y = x * x + p2 ; constant former y = p2 ; la table former y = entry(x).
Quoi smallest lossless théorie ?

Kandidato:
  - entry: theory0, 4 kaj 21
  - theory2 teorio grandeco 2
  - theory0 teorio grandeco 10
  - entry: theory0, 11 kaj 126
  - entry: theory0, 2 kaj 9
  - teorio: theory0, tablo, 0 kaj 0
  - teorio: theory2, square, 4 kaj 7
  - entry: theory0, 0 kaj 5
  - theory3 teorio grandeco 2
  - teorio: theory3, square, 6 kaj 5
  - theory1 teorio grandeco 3
  - entry: theory0, 5 kaj 30
  - teorio: theory1, linear, 6 kaj 8
Datumo:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Regulo: regulo teorio egali lossless iff ĝi predict ĉiu observo ekzakte; regulo elekti lossless teorio de plej malmulta grandeco.
Semantics: linear formi y = p1 * x + p2; square formi y = x * x + p2; constant formi y = p2; tablo formi y = entry(x).
Smallest lossless teorio kio?

Indulók:
  - szócikk: theory0, 4 és 21
  - theory2 elmélet méret 2
  - theory0 elmélet méret 10
  - szócikk: theory0, 11 és 126
  - szócikk: theory0, 2 és 9
  - elmélet: theory0, asztal, 0 és 0
  - elmélet: theory2, square, 4 és 7
  - szócikk: theory0, 0 és 5
  - theory3 elmélet méret 2
  - elmélet: theory3, square, 6 és 5
  - theory1 elmélet méret 3
  - szócikk: theory0, 5 és 30
  - elmélet: theory1, linear, 6 és 8
Adat:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Szabályok:
  - szabály elmélet van veszteségmentes acsa az megjósol minden megfigyelés pontosan
  - szabály kiválaszt a veszteségmentes elmélet of legkisebb méret
Szemantika: linear kialakít y = p1 * x + p2; square kialakít y = x * x + p2; constant kialakít y = p2; a asztal kialakít y = entry(x).
Smallest veszteségmentes elmélet melyik?

候選人:
  - entry:theory0, 4及21
  - theory2theory size2
  - theory0theory size10
  - entry:theory0, 11及126
  - entry:theory0, 2及9
  - theory:theory0, 檯, 0及0
  - theory:theory2, square, 4及7
  - entry:theory0, 0及5
  - theory3theory size2
  - theory:theory3, square, 6及5
  - theory1theory size3
  - entry:theory0, 5及30
  - theory:theory1, linear, 6及8
數據:
  - 4obs21
  - 5obs30
  - 11obs126
  - 0obs5
  - 2obs9
rules:rule:一theory是losslessiffitpredict每observationexactly; rule:揀losslesstheory...嘅leastsize.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; 檯formy = entry(x).
smallest lossless theory乜嘢?

Candidates:
  - entry: theory0, 4 とぅ 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 とぅ 126
  - entry: theory0, 2 とぅ 9
  - theory: theory0, table, 0 とぅ 0
  - theory: theory2, square, 4 とぅ 7
  - entry: theory0, 0 とぅ 5
  - theory3 theory size 2
  - theory: theory3, square, 6 とぅ 5
  - theory1 theory size 3
  - entry: theory0, 5 とぅ 30
  - theory: theory1, linear, 6 とぅ 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Rules: rule theory 有ん lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Үміткер:
  - entry: theory0, 4 және 21
  - theory2 теория мөлшер 2
  - theory0 теория мөлшер 10
  - entry: theory0, 11 және 126
  - entry: theory0, 2 және 9
  - теория: theory0, үстел, 0 және 0
  - теория: theory2, square, 4 және 7
  - entry: theory0, 0 және 5
  - theory3 теория мөлшер 2
  - теория: theory3, square, 6 және 5
  - theory1 теория мөлшер 3
  - entry: theory0, 5 және 30
  - теория: theory1, linear, 6 және 8
Деректер:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Ереже: ереже теория is lossless iff ол predict әр бақылау exactly; ереже таңдау lossless теория туралы least мөлшер.
Семантикалық: linear пішін y = p1 * x + p2; square пішін y = x * x + p2; constant пішін y = p2; үстел пішін y = entry(x).
Smallest lossless теория не?

מועמדת:
  - entry: theory0, 4 וְ־ 21
  - theory2 תּוֹרָה גֹּדֶל 2
  - theory0 תּוֹרָה גֹּדֶל 10
  - entry: theory0, 11 וְ־ 126
  - entry: theory0, 2 וְ־ 9
  - תּוֹרָה: theory0, טַבְלָה, 0 וְ־ 0
  - תּוֹרָה: theory2, square, 4 וְ־ 7
  - entry: theory0, 0 וְ־ 5
  - theory3 תּוֹרָה גֹּדֶל 2
  - תּוֹרָה: theory3, square, 6 וְ־ 5
  - theory1 תּוֹרָה גֹּדֶל 3
  - entry: theory0, 5 וְ־ 30
  - תּוֹרָה: theory1, linear, 6 וְ־ 8
נְתוּנִים:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
מָשַׁל:
  - מָשַׁל אַחַת תּוֹרָה הוא lossless אםם זֶה predict כֹּל תַּצְפִּית בדיוק
  - מָשַׁל בחר ה־ lossless תּוֹרָה שֶׁל least גֹּדֶל
תורת המשמעים: linear צורה y = p1 * x + p2; square צורה y = x * x + p2; constant צורה y = p2; טַבְלָה ה־ צורה y = entry(x).
איזה smallest lossless תּוֹרָה?

Candidates:
  - entry: theory0, 4 დო 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 დო 126
  - entry: theory0, 2 დო 9
  - theory: theory0, table, 0 დო 0
  - theory: theory2, square, 4 დო 7
  - entry: theory0, 0 დო 5
  - theory3 theory size 2
  - theory: theory3, square, 6 დო 5
  - theory1 theory size 3
  - entry: theory0, 5 დო 30
  - theory: theory1, linear, 6 დო 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Kandidat:
  - lema: theory0, 4 dan 21
  - theory2 teori ukuran 2
  - theory0 teori ukuran 10
  - lema: theory0, 11 dan 126
  - lema: theory0, 2 dan 9
  - teori: theory0, meja, 0 dan 0
  - teori: theory2, square, 4 dan 7
  - lema: theory0, 0 dan 5
  - theory3 teori ukuran 2
  - teori: theory3, square, 6 dan 5
  - theory1 teori ukuran 3
  - lema: theory0, 5 dan 30
  - teori: theory1, linear, 6 dan 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Rules:
  - rule teori berada lossless iff it predict setiap observation tepat
  - rule memilih si lossless teori dari least ukuran
Semantik: linear formulir y = p1 * x + p2; square formulir y = x * x + p2; constant formulir y = p2; meja si formulir y = entry(x).
Smallest lossless teori apa?

បេក្ខជន:
  - មេពាក្យ:theory0, 4នឹង21
  - theory2ទ្រឹស្ដីទំហំ2
  - theory0ទ្រឹស្ដីទំហំ10
  - មេពាក្យ:theory0, 11នឹង126
  - មេពាក្យ:theory0, 2នឹង9
  - ទ្រឹស្ដី:theory0, តុ, 0នឹង0
  - ទ្រឹស្ដី:theory2, square, 4នឹង7
  - មេពាក្យ:theory0, 0នឹង5
  - theory3ទ្រឹស្ដីទំហំ2
  - ទ្រឹស្ដី:theory3, square, 6នឹង5
  - theory1ទ្រឹស្ដីទំហំ3
  - មេពាក្យ:theory0, 5នឹង30
  - ទ្រឹស្ដី:theory1, linear, 6នឹង8
ទិន្នន័យ:
  - 4obs21
  - 5obs30
  - 11obs126
  - 0obs5
  - 2obs9
ក្បួន:ក្បួន:ទ្រឹស្ដីត្រូវបានlosslessiffវាចាប់យាមរាល់គំនន់exactly; ក្បួន:រើសthelosslessទ្រឹស្ដីនៃleastទំហំ.
និឃណ្ដសាស្ត្រ:linearគ្រោងy = p1 * x + p2; squareគ្រោងy = x * x + p2; constantគ្រោងy = p2; តុគ្រោងy = entry(x).
smallestlosslessទ្រឹស្ដីអី?

ຜູ້ສະໝັກ:
  - entry:theory0, 4ແລະ21
  - theory2ທິດສະດີຂະຫນາດ2
  - theory0ທິດສະດີຂະຫນາດ10
  - entry:theory0, 11ແລະ126
  - entry:theory0, 2ແລະ9
  - ທິດສະດີ:theory0, ໂຕະ, 0ແລະ0
  - ທິດສະດີ:theory2, square, 4ແລະ7
  - entry:theory0, 0ແລະ5
  - theory3ທິດສະດີຂະຫນາດ2
  - ທິດສະດີ:theory3, square, 6ແລະ5
  - theory1ທິດສະດີຂະຫນາດ3
  - entry:theory0, 5ແລະ30
  - ທິດສະດີ:theory1, linear, 6ແລະ8
ຂໍ້ມູນ:
  - 4obs21
  - 5obs30
  - 11obs126
  - 0obs5
  - 2obs9
ກະຕິກາ:ກະຕິກາ:ທິດສະດີຢູ່losslessiffມັນທຳນວາຍທຸກobservationexactly; ກະຕິກາ:ເລືອກlosslessທິດສະດີຂອງleastຂະຫນາດ.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; ໂຕະformy = entry(x).
smallestlosslessທິດສະດີຫຍັງ?

candidates:
  - entry: theory0, 4 మరియు 21
  - theory2 2 theory size
  - theory0 10 theory size
  - entry: theory0, 11 మరియు 126
  - entry: theory0, 2 మరియు 9
  - theory: theory0, బల్ల, 0 మరియు 0
  - theory: theory2, square, 4 మరియు 7
  - entry: theory0, 0 మరియు 5
  - theory3 2 theory size
  - theory: theory3, square, 6 మరియు 5
  - theory1 3 theory size
  - entry: theory0, 5 మరియు 30
  - theory: theory1, linear, 6 మరియు 8
data:
  - 4 21 obs
  - 5 30 obs
  - 11 126 obs
  - 0 5 obs
  - 2 9 obs
నియమం: నియమం theory ఉండు lossless iff it predict ప్రతి పరిశీలన exactly; నియమం choose lossless theory of least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; బల్ల y = entry(x) form.
smallest lossless theory ఏమిటి?

Candidates:
  - entry: theory0, 4 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 126
  - entry: theory0, 2 9
  - theory: theory0, table, 0 0
  - theory: theory2, square, 4 7
  - entry: theory0, 0 5
  - theory3 theory size 2
  - theory: theory3, square, 6 5
  - theory1 theory size 3
  - entry: theory0, 5 30
  - theory: theory1, linear, 6 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Rules: rule theory wà lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
What smallest lossless theory?

Candidates:
  - entry: theory0, 4 21
  - theory2 2 theory size
  - theory0 10 theory size
  - entry: theory0, 11 126
  - entry: theory0, 2 9
  - theory: theory0, table, 0 0
  - theory: theory2, square, 4 7
  - entry: theory0, 0 5
  - theory3 2 theory size
  - theory: theory3, square, 6 5
  - theory1 3 theory size
  - entry: theory0, 5 30
  - theory: theory1, linear, 6 8
Data:
  - 4 21 obs
  - 5 30 obs
  - 11 126 obs
  - 0 5 obs
  - 2 9 obs
Rules:
  - rule theory naiágúóli lossless iff it predict every observation exactly
  - rule choose the lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

candidates:
  - entry: theory0, 4 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 126
  - entry: theory0, 2 9
  - theory: theory0, table, 0 0
  - theory: theory2, square, 4 7
  - entry: theory0, 0 5
  - theory3 theory size 2
  - theory: theory3, square, 6 5
  - theory1 theory size 3
  - entry: theory0, 5 30
  - theory: theory1, linear, 6 8
data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
smallest lossless theory what?

Candidates:
  - entry: theory0, 4 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 126
  - entry: theory0, 2 9
  - theory: theory0, tafra, 0 0
  - theory: theory2, square, 4 7
  - entry: theory0, 0 5
  - theory3 theory size 2
  - theory: theory3, square, 6 5
  - theory1 theory size 3
  - entry: theory0, 5 30
  - theory: theory1, linear, 6 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; tafra form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory0, 4 21
  - theory2 theory size 2
  - theory0 theory size 10
  - entry: theory0, 11 126
  - entry: theory0, 2 9
  - theory: theory0, táxemésėhestȯtse, 0 0
  - theory: theory2, square, 4 7
  - entry: theory0, 0 5
  - theory3 theory size 2
  - theory: theory3, square, 6 5
  - theory1 theory size 3
  - entry: theory0, 5 30
  - theory: theory1, linear, 6 8
Data:
  - 4 obs 21
  - 5 obs 30
  - 11 obs 126
  - 0 obs 5
  - 2 obs 9
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; táxemésėhestȯtse form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory0, 4 21
  - theory2 2 theory size
  - theory0 10 theory size
  - entry: theory0, 11 126
  - entry: theory0, 2 9
  - theory: theory0, ствал, 0 0
  - theory: theory2, square, 4 7
  - entry: theory0, 0 5
  - theory3 2 theory size
  - theory: theory3, square, 6 5
  - theory1 3 theory size
  - entry: theory0, 5 30
  - theory: theory1, linear, 6 8
Data:
  - 4 21 obs
  - 5 30 obs
  - 11 126 obs
  - 0 5 obs
  - 2 9 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; ствал y = entry(x) form.
Smallest lossless theory вуч?

The candidates are:
  - entry: theory2, 12 and 69
  - entry: theory2, 7 and 44
  - theory: theory1, linear, 5 and 9
  - theory2 theory size 10
  - theory: theory3, square, 4 and -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 and 54
  - theory: theory0, linear, 3 and 11
  - entry: theory2, 3 and 24
  - theory: theory2, table, 0 and 0
  - theory0 theory size 3
  - entry: theory2, 0 and 9
The data are:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

Los candidatos son:
  - la entrada: theory2, 12 y 69
  - la entrada: theory2, 7 y 44
  - la teoría: theory1, linear, 5 y 9
  - theory2 el tamaño de la teoría 10
  - la teoría: theory3, square, 4 y -1
  - theory1 el tamaño de la teoría 3
  - theory3 el tamaño de la teoría 2
  - la entrada: theory2, 9 y 54
  - la teoría: theory0, linear, 3 y 11
  - la entrada: theory2, 3 y 24
  - la teoría: theory2, mesa, 0 y 0
  - theory0 el tamaño de la teoría 3
  - la entrada: theory2, 0 y 9
Los datos son:
  - 12 la observación 69
  - 7 la observación 44
  - 0 la observación 9
  - 9 la observación 54
  - 3 la observación 24
Las reglas son:
  - la regla: a la teoría es lossless si y sólo si it predice every observation exactamente
  - la regla: choose el lossless la teoría de least tamaño
La semántica es: linear la forma y = p1 * x + p2; square la forma y = x * x + p2; constant la forma y = p2; la mesa la forma y = entry(x).
¿Qué smallest lossless la teoría?

候选项如下：
  - 的条目是：theory2、12和69
  - 的条目是：theory2、7和44
  - 的理论是：theory1、linear、5和9
  - theory2的理论规模是10
  - 的理论是：theory3、square、4和-1
  - theory1的理论规模是3
  - theory3的理论规模是2
  - 的条目是：theory2、9和54
  - 的理论是：theory0、linear、3和11
  - 的条目是：theory2、3和24
  - 的理论是：theory2、桌子、0和0
  - theory0的理论规模是3
  - 的条目是：theory2、0和9
数据如下：
  - 12观察到69
  - 7观察到44
  - 0观察到9
  - 9观察到54
  - 3观察到24
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

Adaylar:
  - entry: theory2, 12 ve 69
  - entry: theory2, 7 ve 44
  - kuram: theory1, linear, 5 ve 9
  - theory2 10 kuram boyut
  - kuram: theory3, square, 4 ve -1
  - theory1 3 kuram boyut
  - theory3 2 kuram boyut
  - entry: theory2, 9 ve 54
  - kuram: theory0, linear, 3 ve 11
  - entry: theory2, 3 ve 24
  - kuram: theory2, masa, 0 ve 0
  - theory0 3 kuram boyut
  - entry: theory2, 0 ve 9
Veriler:
  - 12 69 obs
  - 7 44 obs
  - 0 9 obs
  - 9 54 obs
  - 3 24 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

Wagombea ni:
  - entry: theory2, 12 na 69
  - entry: theory2, 7 na 44
  - theory: theory1, linear, 5 na 9
  - theory2 theory size 10
  - theory: theory3, square, 4 na -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 na 54
  - theory: theory0, linear, 3 na 11
  - entry: theory2, 3 na 24
  - theory: theory2, meza, 0 na 0
  - theory0 theory size 3
  - entry: theory2, 0 na 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

The candidates are:
  - entry: theory2, 12 and 69
  - entry: theory2, 7 and 44
  - theory: theory1, linear, 5 and 9
  - theory2 theory size 10
  - theory: theory3, square, 4 and -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 and 54
  - theory: theory0, linear, 3 and 11
  - entry: theory2, 3 and 24
  - theory: theory2, table, 0 and 0
  - theory0 theory size 3
  - entry: theory2, 0 and 9
The data are:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

{candidates: [(entry theory2 12 69) (entry theory2 7 44) (theory theory1 linear 5 9) (theory_size theory2 10) (theory theory3 square 4 -1) (theory_size theory1 3) (theory_size theory3 2) (entry theory2 9 54) (theory theory0 linear 3 11) (entry theory2 3 24) (theory theory2 table 0 0) (theory_size theory0 3) (entry theory2 0 9)], data: [(obs 12 69) (obs 7 44) (obs 0 9) (obs 9 54) (obs 3 24)], query: smallest_lossless_theory, rules: [(rule (a_theory_is_lossless_iff_it_predicts_every_observation_exactly)) (rule (choose_the_lossless_theory_of_least_size))], semantics: [(form linear "y = p1 * x + p2") (form square "y = x * x + p2") (form constant "y = p2") (form table "y = entry(x)")]}

Die Kandidaten sind:
  - Eintrag: theory2, 12 und 69
  - Eintrag: theory2, 7 und 44
  - Theorie: theory1, linear, 5 und 9
  - theory2 Theorie Größe 10
  - Theorie: theory3, square, 4 und -1
  - theory1 Theorie Größe 3
  - theory3 Theorie Größe 2
  - Eintrag: theory2, 9 und 54
  - Theorie: theory0, linear, 3 und 11
  - Eintrag: theory2, 3 und 24
  - Theorie: theory2, Tisch, 0 und 0
  - theory0 Theorie Größe 3
  - Eintrag: theory2, 0 und 9
Die Daten sind:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Die Regeln sind:
  - Regel ein Theorie werden verlustfrei gdw. er vorhersagen jeder Beobachtung genau
  - Regel wählen der verlustfrei Theorie aus geringst Größe
Die Semantik ist: linear formen y = p1 * x + p2; square formen y = x * x + p2; constant formen y = p2; der Tisch formen y = entry(x).
Was smallest verlustfrei Theorie?

Кандѝда̄т:
  - одредница: theory2, 12 и 69
  - одредница: theory2, 7 и 44
  - тѐо̄рија: theory1, linear, 5 и 9
  - theory2 тѐо̄рија величѝна 10
  - тѐо̄рија: theory3, square, 4 и -1
  - theory1 тѐо̄рија величѝна 3
  - theory3 тѐо̄рија величѝна 2
  - одредница: theory2, 9 и 54
  - тѐо̄рија: theory0, linear, 3 и 11
  - одредница: theory2, 3 и 24
  - тѐо̄рија: theory2, сто̑л, 0 и 0
  - theory0 тѐо̄рија величѝна 3
  - одредница: theory2, 0 и 9
Податци:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Пра̏вило:
  - пра̏вило тѐо̄рија би̏ти lossless iff оно predvidjeti сва̏кӣ опа́жа̄ње тачно
  - пра̏вило изабрати lossless тѐо̄рија od minimalan величѝна
Сема̀нтика: linear oblik y = p1 * x + p2; square oblik y = x * x + p2; constant oblik y = p2; сто̑л oblik y = entry(x).
Smallest lossless тѐо̄рија kakav?

Ehdokkaat:
  - artikkeli: theory2, 12 ja 69
  - artikkeli: theory2, 7 ja 44
  - teoria: theory1, linear, 5 ja 9
  - theory2 teoria koko 10
  - teoria: theory3, square, 4 ja -1
  - theory1 teoria koko 3
  - theory3 teoria koko 2
  - artikkeli: theory2, 9 ja 54
  - teoria: theory0, linear, 3 ja 11
  - artikkeli: theory2, 3 ja 24
  - teoria: theory2, pöytä, 0 ja 0
  - theory0 teoria koko 3
  - artikkeli: theory2, 0 ja 9
Tieto:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Säännöt:
  - sääntö teoria tulla häviötön joss se ennakoida jokainen havainnointi täsmälleen
  - sääntö valita häviötön teoria vaille vähin koko
Semantiikka: linear muotoilla y = p1 * x + p2; square muotoilla y = x * x + p2; constant muotoilla y = p2; pöytä muotoilla y = entry(x).
Mikä smallest häviötön teoria?

候选项如下：
  - 的条目是：theory2、12和69
  - 的条目是：theory2、7和44
  - 的理论是：theory1、linear、5和9
  - theory2的理论规模是10
  - 的理论是：theory3、square、4和-1
  - theory1的理论规模是3
  - theory3的理论规模是2
  - 的条目是：theory2、9和54
  - 的理论是：theory0、linear、3和11
  - 的条目是：theory2、3和24
  - 的理论是：theory2、桌子、0和0
  - theory0的理论规模是3
  - 的条目是：theory2、0和9
数据如下：
  - 12观察到69
  - 7观察到44
  - 0观察到9
  - 9观察到54
  - 3观察到24
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

候補者:
  - 項目:theory2, 12と69
  - 項目:theory2, 7と44
  - 理論:theory1, linear, 5と9
  - theory210理論大きさ
  - 理論:theory3, square, 4と-1
  - theory13理論大きさ
  - theory32理論大きさ
  - 項目:theory2, 9と54
  - 理論:theory0, linear, 3と11
  - 項目:theory2, 3と24
  - 理論:theory2, 台, 0と0
  - theory03理論大きさ
  - 項目:theory2, 0と9
資料:
  - 1269obs
  - 744obs
  - 09obs
  - 954obs
  - 324obs
規則:規則:理論れるロスレスiffこれ予言する凡ゆる観察正確に; 規則:選ぶロスレス理論の中の最小の大きさ.
意味論:lineary = p1 * x + p2形作る; squarey = x * x + p2形作る; constanty = p2形作る; 台y = entry(x)形作る.
smallestロスレス理論何と?

Adaylar:
  - entry: theory2, 12 ve 69
  - entry: theory2, 7 ve 44
  - kuram: theory1, linear, 5 ve 9
  - theory2 10 kuram boyut
  - kuram: theory3, square, 4 ve -1
  - theory1 3 kuram boyut
  - theory3 2 kuram boyut
  - entry: theory2, 9 ve 54
  - kuram: theory0, linear, 3 ve 11
  - entry: theory2, 3 ve 24
  - kuram: theory2, masa, 0 ve 0
  - theory0 3 kuram boyut
  - entry: theory2, 0 ve 9
Veriler:
  - 12 69 obs
  - 7 44 obs
  - 0 9 obs
  - 9 54 obs
  - 3 24 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

مُرَشَّح:
  - مَدْخَل: theory2، 12 وَـ 69
  - مَدْخَل: theory2، 7 وَـ 44
  - نَظَرِيَّة: theory1، linear، 5 وَـ 9
  - نَظَرِيَّة مَقَاس theory2 10
  - نَظَرِيَّة: theory3، square، 4 وَـ -1
  - نَظَرِيَّة مَقَاس theory1 3
  - نَظَرِيَّة مَقَاس theory3 2
  - مَدْخَل: theory2، 9 وَـ 54
  - نَظَرِيَّة: theory0، linear، 3 وَـ 11
  - مَدْخَل: theory2، 3 وَـ 24
  - نَظَرِيَّة: theory2، طَاوِلَة، 0 وَـ 0
  - نَظَرِيَّة مَقَاس theory0 3
  - مَدْخَل: theory2، 0 وَـ 9
بَيَانَات:
  - obs 12 69
  - obs 7 44
  - obs 0 9
  - obs 9 54
  - obs 3 24
قَانُون:
  - قَانُون نَظَرِيَّة كَانَ lossless iff هُوَ تَنَبَّأَ كُلّ رَصْد بِالضَّبْط
  - قَانُون اِخْتَارَ الـ lossless نَظَرِيَّة مِنْ أَقَلَّ مَقَاس
عِلْم اَلْمَعَانِي: شَكَّلَ linear y = p1 * x + p2؛ شَكَّلَ square y = x * x + p2؛ شَكَّلَ constant y = p2؛ شَكَّلَ الـ طَاوِلَة y = entry(x).
smallest lossless نَظَرِيَّة مَاذَا؟

Კანდიდატები:
  - სასათაურო სიტყვა: theory2, 12 და 69
  - სასათაურო სიტყვა: theory2, 7 და 44
  - თეორია: theory1, linear, 5 და 9
  - theory2 10 თეორია ზომა
  - თეორია: theory3, square, 4 და -1
  - theory1 3 თეორია ზომა
  - theory3 2 თეორია ზომა
  - სასათაურო სიტყვა: theory2, 9 და 54
  - თეორია: theory0, linear, 3 და 11
  - სასათაურო სიტყვა: theory2, 3 და 24
  - თეორია: theory2, მაგიდა, 0 და 0
  - theory0 3 თეორია ზომა
  - სასათაურო სიტყვა: theory2, 0 და 9
Მონაცემები:
  - 12 69 obs
  - 7 44 obs
  - 0 9 obs
  - 9 54 obs
  - 3 24 obs
Წესი:
  - წესი თეორია ყოფნა უდანაკარგო iff ის predict ყველა დაკვირვება ზუსტად
  - წესი ამორჩევა უდანაკარგო თეორია of least ზომა
Სემანტიკა: linear y = p1 * x + p2 ბლანკი; square y = x * x + p2 ბლანკი; constant y = p2 ბლანკი; მაგიდა y = entry(x) ბლანკი.
Smallest უდანაკარგო თეორია რა?

Kaiwhakauru:
  - tāurunga: theory2, 12 me 69
  - tāurunga: theory2, 7 me 44
  - ariā: theory1, linear, 5 me 9
  - ariā size theory2 10
  - ariā: theory3, square, 4 me -1
  - ariā size theory1 3
  - ariā size theory3 2
  - tāurunga: theory2, 9 me 54
  - ariā: theory0, linear, 3 me 11
  - tāurunga: theory2, 3 me 24
  - ariā: theory2, tēpu, 0 me 0
  - ariā size theory0 3
  - tāurunga: theory2, 0 me 9
Hōtuku:
  - obs 12 69
  - obs 7 44
  - obs 0 9
  - obs 9 54
  - obs 3 24
Rekureihana:
  - rekureihana ariā is lossless iff it matakite every observation pū
  - rekureihana whiri te lossless ariā o least size
Semantics: āhua linear y = p1 * x + p2; āhua square y = x * x + p2; āhua constant y = p2; āhua te tēpu y = entry(x).
Smallest lossless ariā unutai?

Candidates:
  - mục từ: theory2, 12 và 69
  - mục từ: theory2, 7 và 44
  - lý thuyết: theory1, linear, 5 và 9
  - theory2 lý thuyết kích thước 10
  - lý thuyết: theory3, square, 4 và -1
  - theory1 lý thuyết kích thước 3
  - theory3 lý thuyết kích thước 2
  - mục từ: theory2, 9 và 54
  - lý thuyết: theory0, linear, 3 và 11
  - mục từ: theory2, 3 và 24
  - lý thuyết: theory2, bàn, 0 và 0
  - theory0 lý thuyết kích thước 3
  - mục từ: theory2, 0 và 9
Dữ liệu:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Quy tắc:
  - quy tắc lý thuyết được lossless iff nó dự báo mỗi observation đúng rồi
  - quy tắc chọn the lossless lý thuyết bằng least kích thước
Ngữ nghĩa: linear làm thành y = p1 * x + p2; square làm thành y = x * x + p2; constant làm thành y = p2; bàn làm thành y = entry(x).
Smallest lossless lý thuyết gì?

ผู้สมัคร:
  - entry:theory2, 12และ69
  - entry:theory2, 7และ44
  - ทฤษฎี:theory1, linear, 5และ9
  - theory2ทฤษฎีขนาด10
  - ทฤษฎี:theory3, square, 4และ-1
  - theory1ทฤษฎีขนาด3
  - theory3ทฤษฎีขนาด2
  - entry:theory2, 9และ54
  - ทฤษฎี:theory0, linear, 3และ11
  - entry:theory2, 3และ24
  - ทฤษฎี:theory2, โต๊ะ, 0และ0
  - theory0ทฤษฎีขนาด3
  - entry:theory2, 0และ9
ข้อมูล:
  - 12obs69
  - 7obs44
  - 0obs9
  - 9obs54
  - 3obs24
กฎ:กฎ:ทฤษฎีถูกlosslessiffมันทำนายทุกการสังเกตexactly; กฎ:เลือกlosslessทฤษฎีของleastขนาด.
อรรถศาสตร์:linearรูปร่างy = p1 * x + p2; squareรูปร่างy = x * x + p2; constantรูปร่างy = p2; โต๊ะรูปร่างy = entry(x).
smallestlosslessทฤษฎีอะไร?

வேட்பாளர்:
  - உள்நுழைவதற்கு அனுமதி: theory2, 12 மற்றும் 69
  - உள்நுழைவதற்கு அனுமதி: theory2, 7 மற்றும் 44
  - theory: theory1, linear, 5 மற்றும் 9
  - theory2 10 theory size
  - theory: theory3, square, 4 மற்றும் -1
  - theory1 3 theory size
  - theory3 2 theory size
  - உள்நுழைவதற்கு அனுமதி: theory2, 9 மற்றும் 54
  - theory: theory0, linear, 3 மற்றும் 11
  - உள்நுழைவதற்கு அனுமதி: theory2, 3 மற்றும் 24
  - theory: theory2, மேசை, 0 மற்றும் 0
  - theory0 3 theory size
  - உள்நுழைவதற்கு அனுமதி: theory2, 0 மற்றும் 9
தரவுகள்:
  - 12 69 obs
  - 7 44 obs
  - 0 9 obs
  - 9 54 obs
  - 3 24 obs
rules: rule theory படு lossless iff it கணி ஒவ்வொரு observation exactly; rule choose lossless theory கொண்ட least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; மேசை y = entry(x) form.
smallest lossless theory என்ன?

Wagombea ni:
  - entry: theory2, 12 na 69
  - entry: theory2, 7 na 44
  - theory: theory1, linear, 5 na 9
  - theory2 theory size 10
  - theory: theory3, square, 4 na -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 na 54
  - theory: theory0, linear, 3 na 11
  - entry: theory2, 3 na 24
  - theory: theory2, meza, 0 na 0
  - theory0 theory size 3
  - entry: theory2, 0 na 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

Candidates:
  - entry: theory2, 12 dóó 69
  - entry: theory2, 7 dóó 44
  - theory: theory1, linear, 5 dóó 9
  - theory2 10 theory size
  - theory: theory3, square, 4 dóó -1
  - theory1 3 theory size
  - theory3 2 theory size
  - entry: theory2, 9 dóó 54
  - theory: theory0, linear, 3 dóó 11
  - entry: theory2, 3 dóó 24
  - theory: theory2, bikááʼ adání, 0 dóó 0
  - theory0 3 theory size
  - entry: theory2, 0 dóó 9
Data:
  - 12 69 obs
  - 7 44 obs
  - 0 9 obs
  - 9 54 obs
  - 3 24 obs
Bee hazʼáanii:
  - bee hazʼáanii theory átʼé lossless iff it predict every observation exactly
  - bee hazʼáanii choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; bikááʼ adání y = entry(x) form.
Smallest lossless theory haʼátʼíísh?

Candidates:
  - entry: theory2, 12 aamma 69
  - entry: theory2, 7 aamma 44
  - theory: theory1, linear, 5 aamma 9
  - theory2 10 theory size
  - theory: theory3, square, 4 aamma -1
  - theory1 3 theory size
  - theory3 2 theory size
  - entry: theory2, 9 aamma 54
  - theory: theory0, linear, 3 aamma 11
  - entry: theory2, 3 aamma 24
  - theory: theory2, table, 0 aamma 0
  - theory0 3 theory size
  - entry: theory2, 0 aamma 9
Data:
  - 12 69 obs
  - 7 44 obs
  - 0 9 obs
  - 9 54 obs
  - 3 24 obs
Rules: rule theory a lossless iff una predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 blanketti; square y = x * x + p2 blanketti; constant y = p2 blanketti; table y = entry(x) blanketti.
Smallest lossless theory what?

Candidates:
  - entry: theory2, 12 na 69
  - entry: theory2, 7 na 44
  - theory: theory1, linear, 5 na 9
  - theory2 theory size 10
  - theory: theory3, square, 4 na -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 na 54
  - theory: theory0, linear, 3 na 11
  - entry: theory2, 3 na 24
  - theory: theory2, table, 0 na 0
  - theory0 theory size 3
  - entry: theory2, 0 na 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory bilong least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory2, 12 69
  - entry: theory2, 7 44
  - theory: theory1, linear, 5 9
  - theory2 theory size 10
  - theory: theory3, square, 4 -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 54
  - theory: theory0, linear, 3 11
  - entry: theory2, 3 24
  - theory: theory2, table, 0 0
  - theory0 theory size 3
  - entry: theory2, 0 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Nikanixi:
  - nikanixi theory is lossless iff it predict every observation exactly
  - nikanixi choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory kwèch?

Candidates:
  - entry: theory2, 12 а 69
  - entry: theory2, 7 а 44
  - theory: theory1, linear, 5 а 9
  - theory2 theory size 10
  - theory: theory3, square, 4 а -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 а 54
  - theory: theory0, linear, 3 а 11
  - entry: theory2, 3 а 24
  - theory: theory2, table, 0 а 0
  - theory0 theory size 3
  - entry: theory2, 0 а 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Rules:
  - rule theory хила lossless iff it predict дерриг observation exactly
  - rule хержа lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory фу?

후보자:
  - 항목: theory2, 12 69
  - 항목: theory2, 7 44
  - 이론: theory1, linear, 5 9
  - theory2 10 이론 크기
  - 이론: theory3, square, 4 -1
  - theory1 3 이론 크기
  - theory3 2 이론 크기
  - 항목: theory2, 9 54
  - 이론: theory0, linear, 3 11
  - 항목: theory2, 3 24
  - 이론: theory2, 테이블, 0 0
  - theory0 3 이론 크기
  - 항목: theory2, 0 9
자료:
  - 12 69 obs
  - 7 44 obs
  - 0 9 obs
  - 9 54 obs
  - 3 24 obs
규칙: 규칙 이론 is lossless iff 이것 예언하다 각 관찰 정확하게; 규칙 고르다 lossless 이론...의 가장 적게 크기.
의미론: linear y = p1 * x + p2 형상; square y = x * x + p2 형상; constant y = p2 형상; 테이블 y = entry(x) 형상.
smallest lossless 이론 무엇?

Kandidatu:
  - sarrera: theory2, 12 eta 69
  - sarrera: theory2, 7 eta 44
  - theory: theory1, linear, 5 eta 9
  - theory2 10 theory tamaina
  - theory: theory3, square, 4 eta -1
  - theory1 3 theory tamaina
  - theory3 2 theory tamaina
  - sarrera: theory2, 9 eta 54
  - theory: theory0, linear, 3 eta 11
  - sarrera: theory2, 3 eta 24
  - theory: theory2, mahai, 0 eta 0
  - theory0 3 theory tamaina
  - sarrera: theory2, 0 eta 9
Data:
  - 12 69 obs
  - 7 44 obs
  - 0 9 obs
  - 9 54 obs
  - 3 24 obs
Arau:
  - arau bat theory izan lossless iff it aurresan every observation exactly
  - arau aukeratu the lossless theory of least tamaina
Semantics: linear y = p1 * x + p2 forma; square y = x * x + p2 forma; constant y = p2 forma; mahai y = entry(x) forma.
Smallest lossless theory zer?

ᎠᏙᎩᏯᏍᎩ:
  - entry: theory2, 12 ᎠᎴ 69
  - entry: theory2, 7 ᎠᎴ 44
  - theory: theory1, linear, 5 ᎠᎴ 9
  - theory2 theory size 10
  - theory: theory3, square, 4 ᎠᎴ -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 ᎠᎴ 54
  - theory: theory0, linear, 3 ᎠᎴ 11
  - entry: theory2, 3 ᎠᎴ 24
  - theory: theory2, ᎦᏍᎩᎶ, 0 ᎠᎴ 0
  - theory0 theory size 3
  - entry: theory2, 0 ᎠᎴ 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ᎦᏍᎩᎶ form y = entry(x).
What smallest lossless theory?

Candidates:
  - entry: theory2, 12 69
  - entry: theory2, 7 44
  - theory: theory1, linear, 5 9
  - theory2 theory chhika 10
  - theory: theory3, square, 4 -1
  - theory1 theory chhika 3
  - theory3 theory chhika 2
  - entry: theory2, 9 54
  - theory: theory0, linear, 3 11
  - entry: theory2, 3 24
  - theory: theory2, patacha, 0 0
  - theory0 theory chhika 3
  - entry: theory2, 0 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Rules:
  - rule theory tiyay lossless iff it predict tukuy observation exactly
  - rule akllay lossless theory of least chhika
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; patacha form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory2, 12 ыкӏи 69
  - entry: theory2, 7 ыкӏи 44
  - тиориэ: theory1, linear, 5 ыкӏи 9
  - theory2 10 тиориэ size
  - тиориэ: theory3, square, 4 ыкӏи -1
  - theory1 3 тиориэ size
  - theory3 2 тиориэ size
  - entry: theory2, 9 ыкӏи 54
  - тиориэ: theory0, linear, 3 ыкӏи 11
  - entry: theory2, 3 ыкӏи 24
  - тиориэ: theory2, table, 0 ыкӏи 0
  - theory0 3 тиориэ size
  - entry: theory2, 0 ыкӏи 9
Data:
  - 12 69 obs
  - 7 44 obs
  - 0 9 obs
  - 9 54 obs
  - 3 24 obs
Rules: rule тиориэ is lossless iff it predict every observation exactly; rule choose the lossless тиориэ of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless тиориэ сыд?

Candidates:
  - entry: theory2, 12 thiab 69
  - entry: theory2, 7 thiab 44
  - theory: theory1, linear, 5 thiab 9
  - theory2 theory size 10
  - theory: theory3, square, 4 thiab -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 thiab 54
  - theory: theory0, linear, 3 thiab 11
  - entry: theory2, 3 thiab 24
  - theory: theory2, rooj, 0 thiab 0
  - theory0 theory size 3
  - entry: theory2, 0 thiab 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Cai: cai theory is lossless iff nws predict every observation exactly; cai choose lossless theory of least size.
Lub ntsiab: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; rooj form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory2, 12 69
  - entry: theory2, 7 44
  - theory: theory1, linear, 5 9
  - theory2 theory size 10
  - theory: theory3, square, 4 -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 54
  - theory: theory0, linear, 3 11
  - entry: theory2, 3 24
  - theory: theory2, table, 0 0
  - theory0 theory size 3
  - entry: theory2, 0 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of wy krook size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory ining-jak?

Candidates:
  - entry: theory2, 12 micha' 69
  - entry: theory2, 7 micha' 44
  - theory: theory1, linear, 5 micha' 9
  - theory2 theory size 10
  - theory: theory3, square, 4 micha' -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 micha' 54
  - theory: theory0, linear, 3 micha' 11
  - entry: theory2, 3 micha' 24
  - theory: theory2, table, 0 micha' 0
  - theory0 theory size 3
  - entry: theory2, 0 micha' 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory nanta?

Candidates:
  - entry: theory2, 12 カ 69
  - entry: theory2, 7 カ 44
  - theory: theory1, linear, 5 カ 9
  - theory2 10 theory size
  - theory: theory3, square, 4 カ -1
  - theory1 3 theory size
  - theory3 2 theory size
  - entry: theory2, 9 カ 54
  - theory: theory0, linear, 3 カ 11
  - entry: theory2, 3 カ 24
  - theory: theory2, table, 0 カ 0
  - theory0 3 theory size
  - entry: theory2, 0 カ 9
Data:
  - 12 69 obs
  - 7 44 obs
  - 0 9 obs
  - 9 54 obs
  - 3 24 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 ノカ; square y = x * x + p2 ノカ; constant y = p2 ノカ; table y = entry(x) ノカ.
Smallest lossless theory what?

Candidates:
  - entry: theory2, 12 ынкъам 69
  - entry: theory2, 7 ынкъам 44
  - theory: theory1, linear, 5 ынкъам 9
  - theory2 theory size 10
  - theory: theory3, square, 4 ынкъам -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 ынкъам 54
  - theory: theory0, linear, 3 ынкъам 11
  - entry: theory2, 3 ынкъам 24
  - theory: theory2, table, 0 ынкъам 0
  - theory0 theory size 3
  - entry: theory2, 0 ынкъам 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory2, 12 yéetel 69
  - entry: theory2, 7 yéetel 44
  - theory: theory1, linear, 5 yéetel 9
  - theory2 theory size 10
  - theory: theory3, square, 4 yéetel -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 yéetel 54
  - theory: theory0, linear, 3 yéetel 11
  - entry: theory2, 3 yéetel 24
  - theory: theory2, table, 0 yéetel 0
  - theory0 theory size 3
  - entry: theory2, 0 yéetel 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Rules:
  - rule theory yan lossless iff it predict every observation exactly
  - rule yéey lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory2, 12 69
  - entry: theory2, 7 44
  - theory: theory1, linear, 5 9
  - theory2 theory size 10
  - theory: theory3, square, 4 -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 54
  - theory: theory0, linear, 3 11
  - entry: theory2, 3 24
  - theory: theory2, mę́soną, 0 0
  - theory0 theory size 3
  - entry: theory2, 0 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Rules:
  - rule theory is lossless iff ą́wąną predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mę́soną form y = entry(x).
Smallest lossless theory híli?

Candidates:
  - entry: theory2, 12 na 69
  - entry: theory2, 7 na 44
  - theory: theory1, linear, 5 na 9
  - theory2 10 theory size
  - theory: theory3, square, 4 na -1
  - theory1 3 theory size
  - theory3 2 theory size
  - entry: theory2, 9 na 54
  - theory: theory0, linear, 3 na 11
  - entry: theory2, 3 na 24
  - theory: theory2, table, 0 na 0
  - theory0 3 theory size
  - entry: theory2, 0 na 9
Data:
  - 12 69 obs
  - 7 44 obs
  - 0 9 obs
  - 9 54 obs
  - 3 24 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory2, 12 69
  - entry: theory2, 7 44
  - theory: theory1, linear, 5 9
  - theory2 theory size 10
  - theory: theory3, square, 4 -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 54
  - theory: theory0, linear, 3 11
  - entry: theory2, 3 24
  - theory: theory2, table, 0 0
  - theory0 theory size 3
  - entry: theory2, 0 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory2, 12 69
  - entry: theory2, 7 44
  - theory: theory1, linear, 5 9
  - theory2 10 theory size
  - theory: theory3, square, 4 -1
  - theory1 3 theory size
  - theory3 2 theory size
  - entry: theory2, 9 54
  - theory: theory0, linear, 3 11
  - entry: theory2, 3 24
  - theory: theory2, table, 0 0
  - theory0 3 theory size
  - entry: theory2, 0 9
Data:
  - 12 69 obs
  - 7 44 obs
  - 0 9 obs
  - 9 54 obs
  - 3 24 obs
Rules:
  - rule maya theory is lossless iff it predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory2, 12 ǂʻá 69
  - entry: theory2, 7 ǂʻá 44
  - theory: theory1, linear, 5 ǂʻá 9
  - theory2 theory ʻǁnàhã 10
  - theory: theory3, square, 4 ǂʻá -1
  - theory1 theory ʻǁnàhã 3
  - theory3 theory ʻǁnàhã 2
  - entry: theory2, 9 ǂʻá 54
  - theory: theory0, linear, 3 ǂʻá 11
  - entry: theory2, 3 ǂʻá 24
  - theory: theory2, table, 0 ǂʻá 0
  - theory0 theory ʻǁnàhã 3
  - entry: theory2, 0 ǂʻá 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Rules:
  - rule theory ǀîi lossless iff èh predict every observation exactly
  - rule choose lossless theory of least ʻǁnàhã
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory2, 12 69
  - entry: theory2, 7 44
  - theory: theory1, linear, 5 9
  - theory2 10 theory size
  - theory: theory3, square, 4 -1
  - theory1 3 theory size
  - theory3 2 theory size
  - entry: theory2, 9 54
  - theory: theory0, linear, 3 11
  - entry: theory2, 3 24
  - theory: theory2, остол, 0 0
  - theory0 3 theory size
  - entry: theory2, 0 9
Data:
  - 12 69 obs
  - 7 44 obs
  - 0 9 obs
  - 9 54 obs
  - 3 24 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; остол y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory2, 12 69
  - entry: theory2, 7 44
  - theory: theory1, linear, 5 9
  - theory2 theory size 10
  - theory: theory3, square, 4 -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 54
  - theory: theory0, linear, 3 11
  - entry: theory2, 3 24
  - theory: theory2, table, 0 0
  - theory0 theory size 3
  - entry: theory2, 0 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory2, 12 69
  - entry: theory2, 7 44
  - theory: theory1, linear, 5 9
  - theory2 10 theory size
  - theory: theory3, square, 4 -1
  - theory1 3 theory size
  - theory3 2 theory size
  - entry: theory2, 9 54
  - theory: theory0, linear, 3 11
  - entry: theory2, 3 24
  - theory: theory2, table, 0 0
  - theory0 3 theory size
  - entry: theory2, 0 9
Data:
  - 12 69 obs
  - 7 44 obs
  - 0 9 obs
  - 9 54 obs
  - 3 24 obs
Rules:
  - rule theory is lossless iff kitu predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory2, 12 69
  - entry: theory2, 7 44
  - theory: theory1, linear, 5 9
  - theory2 theory size 10
  - theory: theory3, square, 4 -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 54
  - theory: theory0, linear, 3 11
  - entry: theory2, 3 24
  - theory: theory2, mesa, 0 0
  - theory0 theory size 3
  - entry: theory2, 0 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mesa form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory2, 12 69
  - entry: theory2, 7 44
  - theory: theory1, linear, 5 9
  - theory2 theory size 10
  - theory: theory3, square, 4 -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 54
  - theory: theory0, linear, 3 11
  - entry: theory2, 3 24
  - theory: theory2, table, 0 0
  - theory0 theory size 3
  - entry: theory2, 0 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Rules:
  - rule theory nemi lossless iff yaja predict every observation exactly
  - rule choose ne lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ne table form y = entry(x).
Smallest lossless theory tay?

Les candidats sont:
  - article: theory2, 12 et 69
  - article: theory2, 7 et 44
  - théorie: theory1, linear, 5 et 9
  - theory2 théorie taille 10
  - théorie: theory3, square, 4 et -1
  - theory1 théorie taille 3
  - theory3 théorie taille 2
  - article: theory2, 9 et 54
  - théorie: theory0, linear, 3 et 11
  - article: theory2, 3 et 24
  - théorie: theory2, table, 0 et 0
  - theory0 théorie taille 3
  - article: theory2, 0 et 9
Les données sont:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Les règles sont:
  - règle un théorie être lossless ssi il prédire tout observation exactement
  - règle choisir le lossless théorie du moindre taille
La sémantique est : linear former y = p1 * x + p2 ; square former y = x * x + p2 ; constant former y = p2 ; la table former y = entry(x).
Quoi smallest lossless théorie ?

Kandidato:
  - entry: theory2, 12 kaj 69
  - entry: theory2, 7 kaj 44
  - teorio: theory1, linear, 5 kaj 9
  - theory2 teorio grandeco 10
  - teorio: theory3, square, 4 kaj -1
  - theory1 teorio grandeco 3
  - theory3 teorio grandeco 2
  - entry: theory2, 9 kaj 54
  - teorio: theory0, linear, 3 kaj 11
  - entry: theory2, 3 kaj 24
  - teorio: theory2, tablo, 0 kaj 0
  - theory0 teorio grandeco 3
  - entry: theory2, 0 kaj 9
Datumo:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Regulo: regulo teorio egali lossless iff ĝi predict ĉiu observo ekzakte; regulo elekti lossless teorio de plej malmulta grandeco.
Semantics: linear formi y = p1 * x + p2; square formi y = x * x + p2; constant formi y = p2; tablo formi y = entry(x).
Smallest lossless teorio kio?

Indulók:
  - szócikk: theory2, 12 és 69
  - szócikk: theory2, 7 és 44
  - elmélet: theory1, linear, 5 és 9
  - theory2 elmélet méret 10
  - elmélet: theory3, square, 4 és -1
  - theory1 elmélet méret 3
  - theory3 elmélet méret 2
  - szócikk: theory2, 9 és 54
  - elmélet: theory0, linear, 3 és 11
  - szócikk: theory2, 3 és 24
  - elmélet: theory2, asztal, 0 és 0
  - theory0 elmélet méret 3
  - szócikk: theory2, 0 és 9
Adat:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Szabályok:
  - szabály elmélet van veszteségmentes acsa az megjósol minden megfigyelés pontosan
  - szabály kiválaszt a veszteségmentes elmélet of legkisebb méret
Szemantika: linear kialakít y = p1 * x + p2; square kialakít y = x * x + p2; constant kialakít y = p2; a asztal kialakít y = entry(x).
Smallest veszteségmentes elmélet melyik?

候選人:
  - entry:theory2, 12及69
  - entry:theory2, 7及44
  - theory:theory1, linear, 5及9
  - theory2theory size10
  - theory:theory3, square, 4及-1
  - theory1theory size3
  - theory3theory size2
  - entry:theory2, 9及54
  - theory:theory0, linear, 3及11
  - entry:theory2, 3及24
  - theory:theory2, 檯, 0及0
  - theory0theory size3
  - entry:theory2, 0及9
數據:
  - 12obs69
  - 7obs44
  - 0obs9
  - 9obs54
  - 3obs24
rules:rule:一theory是losslessiffitpredict每observationexactly; rule:揀losslesstheory...嘅leastsize.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; 檯formy = entry(x).
smallest lossless theory乜嘢?

Candidates:
  - entry: theory2, 12 とぅ 69
  - entry: theory2, 7 とぅ 44
  - theory: theory1, linear, 5 とぅ 9
  - theory2 theory size 10
  - theory: theory3, square, 4 とぅ -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 とぅ 54
  - theory: theory0, linear, 3 とぅ 11
  - entry: theory2, 3 とぅ 24
  - theory: theory2, table, 0 とぅ 0
  - theory0 theory size 3
  - entry: theory2, 0 とぅ 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Rules: rule theory 有ん lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Үміткер:
  - entry: theory2, 12 және 69
  - entry: theory2, 7 және 44
  - теория: theory1, linear, 5 және 9
  - theory2 теория мөлшер 10
  - теория: theory3, square, 4 және -1
  - theory1 теория мөлшер 3
  - theory3 теория мөлшер 2
  - entry: theory2, 9 және 54
  - теория: theory0, linear, 3 және 11
  - entry: theory2, 3 және 24
  - теория: theory2, үстел, 0 және 0
  - theory0 теория мөлшер 3
  - entry: theory2, 0 және 9
Деректер:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Ереже: ереже теория is lossless iff ол predict әр бақылау exactly; ереже таңдау lossless теория туралы least мөлшер.
Семантикалық: linear пішін y = p1 * x + p2; square пішін y = x * x + p2; constant пішін y = p2; үстел пішін y = entry(x).
Smallest lossless теория не?

מועמדת:
  - entry: theory2, 12 וְ־ 69
  - entry: theory2, 7 וְ־ 44
  - תּוֹרָה: theory1, linear, 5 וְ־ 9
  - theory2 תּוֹרָה גֹּדֶל 10
  - תּוֹרָה: theory3, square, 4 וְ־ -1
  - theory1 תּוֹרָה גֹּדֶל 3
  - theory3 תּוֹרָה גֹּדֶל 2
  - entry: theory2, 9 וְ־ 54
  - תּוֹרָה: theory0, linear, 3 וְ־ 11
  - entry: theory2, 3 וְ־ 24
  - תּוֹרָה: theory2, טַבְלָה, 0 וְ־ 0
  - theory0 תּוֹרָה גֹּדֶל 3
  - entry: theory2, 0 וְ־ 9
נְתוּנִים:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
מָשַׁל:
  - מָשַׁל אַחַת תּוֹרָה הוא lossless אםם זֶה predict כֹּל תַּצְפִּית בדיוק
  - מָשַׁל בחר ה־ lossless תּוֹרָה שֶׁל least גֹּדֶל
תורת המשמעים: linear צורה y = p1 * x + p2; square צורה y = x * x + p2; constant צורה y = p2; טַבְלָה ה־ צורה y = entry(x).
איזה smallest lossless תּוֹרָה?

Candidates:
  - entry: theory2, 12 დო 69
  - entry: theory2, 7 დო 44
  - theory: theory1, linear, 5 დო 9
  - theory2 theory size 10
  - theory: theory3, square, 4 დო -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 დო 54
  - theory: theory0, linear, 3 დო 11
  - entry: theory2, 3 დო 24
  - theory: theory2, table, 0 დო 0
  - theory0 theory size 3
  - entry: theory2, 0 დო 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Kandidat:
  - lema: theory2, 12 dan 69
  - lema: theory2, 7 dan 44
  - teori: theory1, linear, 5 dan 9
  - theory2 teori ukuran 10
  - teori: theory3, square, 4 dan -1
  - theory1 teori ukuran 3
  - theory3 teori ukuran 2
  - lema: theory2, 9 dan 54
  - teori: theory0, linear, 3 dan 11
  - lema: theory2, 3 dan 24
  - teori: theory2, meja, 0 dan 0
  - theory0 teori ukuran 3
  - lema: theory2, 0 dan 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Rules:
  - rule teori berada lossless iff it predict setiap observation tepat
  - rule memilih si lossless teori dari least ukuran
Semantik: linear formulir y = p1 * x + p2; square formulir y = x * x + p2; constant formulir y = p2; meja si formulir y = entry(x).
Smallest lossless teori apa?

បេក្ខជន:
  - មេពាក្យ:theory2, 12នឹង69
  - មេពាក្យ:theory2, 7នឹង44
  - ទ្រឹស្ដី:theory1, linear, 5នឹង9
  - theory2ទ្រឹស្ដីទំហំ10
  - ទ្រឹស្ដី:theory3, square, 4នឹង-1
  - theory1ទ្រឹស្ដីទំហំ3
  - theory3ទ្រឹស្ដីទំហំ2
  - មេពាក្យ:theory2, 9នឹង54
  - ទ្រឹស្ដី:theory0, linear, 3នឹង11
  - មេពាក្យ:theory2, 3នឹង24
  - ទ្រឹស្ដី:theory2, តុ, 0នឹង0
  - theory0ទ្រឹស្ដីទំហំ3
  - មេពាក្យ:theory2, 0នឹង9
ទិន្នន័យ:
  - 12obs69
  - 7obs44
  - 0obs9
  - 9obs54
  - 3obs24
ក្បួន:ក្បួន:ទ្រឹស្ដីត្រូវបានlosslessiffវាចាប់យាមរាល់គំនន់exactly; ក្បួន:រើសthelosslessទ្រឹស្ដីនៃleastទំហំ.
និឃណ្ដសាស្ត្រ:linearគ្រោងy = p1 * x + p2; squareគ្រោងy = x * x + p2; constantគ្រោងy = p2; តុគ្រោងy = entry(x).
smallestlosslessទ្រឹស្ដីអី?

ຜູ້ສະໝັກ:
  - entry:theory2, 12ແລະ69
  - entry:theory2, 7ແລະ44
  - ທິດສະດີ:theory1, linear, 5ແລະ9
  - theory2ທິດສະດີຂະຫນາດ10
  - ທິດສະດີ:theory3, square, 4ແລະ-1
  - theory1ທິດສະດີຂະຫນາດ3
  - theory3ທິດສະດີຂະຫນາດ2
  - entry:theory2, 9ແລະ54
  - ທິດສະດີ:theory0, linear, 3ແລະ11
  - entry:theory2, 3ແລະ24
  - ທິດສະດີ:theory2, ໂຕະ, 0ແລະ0
  - theory0ທິດສະດີຂະຫນາດ3
  - entry:theory2, 0ແລະ9
ຂໍ້ມູນ:
  - 12obs69
  - 7obs44
  - 0obs9
  - 9obs54
  - 3obs24
ກະຕິກາ:ກະຕິກາ:ທິດສະດີຢູ່losslessiffມັນທຳນວາຍທຸກobservationexactly; ກະຕິກາ:ເລືອກlosslessທິດສະດີຂອງleastຂະຫນາດ.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; ໂຕະformy = entry(x).
smallestlosslessທິດສະດີຫຍັງ?

candidates:
  - entry: theory2, 12 మరియు 69
  - entry: theory2, 7 మరియు 44
  - theory: theory1, linear, 5 మరియు 9
  - theory2 10 theory size
  - theory: theory3, square, 4 మరియు -1
  - theory1 3 theory size
  - theory3 2 theory size
  - entry: theory2, 9 మరియు 54
  - theory: theory0, linear, 3 మరియు 11
  - entry: theory2, 3 మరియు 24
  - theory: theory2, బల్ల, 0 మరియు 0
  - theory0 3 theory size
  - entry: theory2, 0 మరియు 9
data:
  - 12 69 obs
  - 7 44 obs
  - 0 9 obs
  - 9 54 obs
  - 3 24 obs
నియమం: నియమం theory ఉండు lossless iff it predict ప్రతి పరిశీలన exactly; నియమం choose lossless theory of least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; బల్ల y = entry(x) form.
smallest lossless theory ఏమిటి?

Candidates:
  - entry: theory2, 12 69
  - entry: theory2, 7 44
  - theory: theory1, linear, 5 9
  - theory2 theory size 10
  - theory: theory3, square, 4 -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 54
  - theory: theory0, linear, 3 11
  - entry: theory2, 3 24
  - theory: theory2, table, 0 0
  - theory0 theory size 3
  - entry: theory2, 0 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Rules: rule theory wà lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
What smallest lossless theory?

Candidates:
  - entry: theory2, 12 69
  - entry: theory2, 7 44
  - theory: theory1, linear, 5 9
  - theory2 10 theory size
  - theory: theory3, square, 4 -1
  - theory1 3 theory size
  - theory3 2 theory size
  - entry: theory2, 9 54
  - theory: theory0, linear, 3 11
  - entry: theory2, 3 24
  - theory: theory2, table, 0 0
  - theory0 3 theory size
  - entry: theory2, 0 9
Data:
  - 12 69 obs
  - 7 44 obs
  - 0 9 obs
  - 9 54 obs
  - 3 24 obs
Rules:
  - rule theory naiágúóli lossless iff it predict every observation exactly
  - rule choose the lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

candidates:
  - entry: theory2, 12 69
  - entry: theory2, 7 44
  - theory: theory1, linear, 5 9
  - theory2 theory size 10
  - theory: theory3, square, 4 -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 54
  - theory: theory0, linear, 3 11
  - entry: theory2, 3 24
  - theory: theory2, table, 0 0
  - theory0 theory size 3
  - entry: theory2, 0 9
data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
smallest lossless theory what?

Candidates:
  - entry: theory2, 12 69
  - entry: theory2, 7 44
  - theory: theory1, linear, 5 9
  - theory2 theory size 10
  - theory: theory3, square, 4 -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 54
  - theory: theory0, linear, 3 11
  - entry: theory2, 3 24
  - theory: theory2, tafra, 0 0
  - theory0 theory size 3
  - entry: theory2, 0 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; tafra form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory2, 12 69
  - entry: theory2, 7 44
  - theory: theory1, linear, 5 9
  - theory2 theory size 10
  - theory: theory3, square, 4 -1
  - theory1 theory size 3
  - theory3 theory size 2
  - entry: theory2, 9 54
  - theory: theory0, linear, 3 11
  - entry: theory2, 3 24
  - theory: theory2, táxemésėhestȯtse, 0 0
  - theory0 theory size 3
  - entry: theory2, 0 9
Data:
  - 12 obs 69
  - 7 obs 44
  - 0 obs 9
  - 9 obs 54
  - 3 obs 24
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; táxemésėhestȯtse form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory2, 12 69
  - entry: theory2, 7 44
  - theory: theory1, linear, 5 9
  - theory2 10 theory size
  - theory: theory3, square, 4 -1
  - theory1 3 theory size
  - theory3 2 theory size
  - entry: theory2, 9 54
  - theory: theory0, linear, 3 11
  - entry: theory2, 3 24
  - theory: theory2, ствал, 0 0
  - theory0 3 theory size
  - entry: theory2, 0 9
Data:
  - 12 69 obs
  - 7 44 obs
  - 0 9 obs
  - 9 54 obs
  - 3 24 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; ствал y = entry(x) form.
Smallest lossless theory вуч?

The candidates are:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 and 17
  - theory: theory1, square, 5 and 6
  - entry: theory3, 2 and 12
  - theory: theory3, table, 0 and 0
  - entry: theory3, 7 and 57
  - theory2 theory size 2
  - theory: theory2, square, 6 and 8
  - theory: theory0, linear, 6 and 9
  - entry: theory3, 8 and 72
  - entry: theory3, 9 and 89
  - theory3 theory size 10
The data are:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

Los candidatos son:
  - theory0 el tamaño de la teoría 3
  - theory1 el tamaño de la teoría 2
  - la entrada: theory3, 3 y 17
  - la teoría: theory1, square, 5 y 6
  - la entrada: theory3, 2 y 12
  - la teoría: theory3, mesa, 0 y 0
  - la entrada: theory3, 7 y 57
  - theory2 el tamaño de la teoría 2
  - la teoría: theory2, square, 6 y 8
  - la teoría: theory0, linear, 6 y 9
  - la entrada: theory3, 8 y 72
  - la entrada: theory3, 9 y 89
  - theory3 el tamaño de la teoría 10
Los datos son:
  - 3 la observación 17
  - 8 la observación 72
  - 9 la observación 89
  - 2 la observación 12
  - 7 la observación 57
Las reglas son:
  - la regla: a la teoría es lossless si y sólo si it predice every observation exactamente
  - la regla: choose el lossless la teoría de least tamaño
La semántica es: linear la forma y = p1 * x + p2; square la forma y = x * x + p2; constant la forma y = p2; la mesa la forma y = entry(x).
¿Qué smallest lossless la teoría?

候选项如下：
  - theory0的理论规模是3
  - theory1的理论规模是2
  - 的条目是：theory3、3和17
  - 的理论是：theory1、square、5和6
  - 的条目是：theory3、2和12
  - 的理论是：theory3、桌子、0和0
  - 的条目是：theory3、7和57
  - theory2的理论规模是2
  - 的理论是：theory2、square、6和8
  - 的理论是：theory0、linear、6和9
  - 的条目是：theory3、8和72
  - 的条目是：theory3、9和89
  - theory3的理论规模是10
数据如下：
  - 3观察到17
  - 8观察到72
  - 9观察到89
  - 2观察到12
  - 7观察到57
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

Adaylar:
  - theory0 3 kuram boyut
  - theory1 2 kuram boyut
  - entry: theory3, 3 ve 17
  - kuram: theory1, square, 5 ve 6
  - entry: theory3, 2 ve 12
  - kuram: theory3, masa, 0 ve 0
  - entry: theory3, 7 ve 57
  - theory2 2 kuram boyut
  - kuram: theory2, square, 6 ve 8
  - kuram: theory0, linear, 6 ve 9
  - entry: theory3, 8 ve 72
  - entry: theory3, 9 ve 89
  - theory3 10 kuram boyut
Veriler:
  - 3 17 obs
  - 8 72 obs
  - 9 89 obs
  - 2 12 obs
  - 7 57 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

Wagombea ni:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 na 17
  - theory: theory1, square, 5 na 6
  - entry: theory3, 2 na 12
  - theory: theory3, meza, 0 na 0
  - entry: theory3, 7 na 57
  - theory2 theory size 2
  - theory: theory2, square, 6 na 8
  - theory: theory0, linear, 6 na 9
  - entry: theory3, 8 na 72
  - entry: theory3, 9 na 89
  - theory3 theory size 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

The candidates are:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 and 17
  - theory: theory1, square, 5 and 6
  - entry: theory3, 2 and 12
  - theory: theory3, table, 0 and 0
  - entry: theory3, 7 and 57
  - theory2 theory size 2
  - theory: theory2, square, 6 and 8
  - theory: theory0, linear, 6 and 9
  - entry: theory3, 8 and 72
  - entry: theory3, 9 and 89
  - theory3 theory size 10
The data are:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

{candidates: [(theory_size theory0 3) (theory_size theory1 2) (entry theory3 3 17) (theory theory1 square 5 6) (entry theory3 2 12) (theory theory3 table 0 0) (entry theory3 7 57) (theory_size theory2 2) (theory theory2 square 6 8) (theory theory0 linear 6 9) (entry theory3 8 72) (entry theory3 9 89) (theory_size theory3 10)], data: [(obs 3 17) (obs 8 72) (obs 9 89) (obs 2 12) (obs 7 57)], query: smallest_lossless_theory, rules: [(rule (a_theory_is_lossless_iff_it_predicts_every_observation_exactly)) (rule (choose_the_lossless_theory_of_least_size))], semantics: [(form linear "y = p1 * x + p2") (form square "y = x * x + p2") (form constant "y = p2") (form table "y = entry(x)")]}

Die Kandidaten sind:
  - theory0 Theorie Größe 3
  - theory1 Theorie Größe 2
  - Eintrag: theory3, 3 und 17
  - Theorie: theory1, square, 5 und 6
  - Eintrag: theory3, 2 und 12
  - Theorie: theory3, Tisch, 0 und 0
  - Eintrag: theory3, 7 und 57
  - theory2 Theorie Größe 2
  - Theorie: theory2, square, 6 und 8
  - Theorie: theory0, linear, 6 und 9
  - Eintrag: theory3, 8 und 72
  - Eintrag: theory3, 9 und 89
  - theory3 Theorie Größe 10
Die Daten sind:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Die Regeln sind:
  - Regel ein Theorie werden verlustfrei gdw. er vorhersagen jeder Beobachtung genau
  - Regel wählen der verlustfrei Theorie aus geringst Größe
Die Semantik ist: linear formen y = p1 * x + p2; square formen y = x * x + p2; constant formen y = p2; der Tisch formen y = entry(x).
Was smallest verlustfrei Theorie?

Кандѝда̄т:
  - theory0 тѐо̄рија величѝна 3
  - theory1 тѐо̄рија величѝна 2
  - одредница: theory3, 3 и 17
  - тѐо̄рија: theory1, square, 5 и 6
  - одредница: theory3, 2 и 12
  - тѐо̄рија: theory3, сто̑л, 0 и 0
  - одредница: theory3, 7 и 57
  - theory2 тѐо̄рија величѝна 2
  - тѐо̄рија: theory2, square, 6 и 8
  - тѐо̄рија: theory0, linear, 6 и 9
  - одредница: theory3, 8 и 72
  - одредница: theory3, 9 и 89
  - theory3 тѐо̄рија величѝна 10
Податци:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Пра̏вило:
  - пра̏вило тѐо̄рија би̏ти lossless iff оно predvidjeti сва̏кӣ опа́жа̄ње тачно
  - пра̏вило изабрати lossless тѐо̄рија od minimalan величѝна
Сема̀нтика: linear oblik y = p1 * x + p2; square oblik y = x * x + p2; constant oblik y = p2; сто̑л oblik y = entry(x).
Smallest lossless тѐо̄рија kakav?

Ehdokkaat:
  - theory0 teoria koko 3
  - theory1 teoria koko 2
  - artikkeli: theory3, 3 ja 17
  - teoria: theory1, square, 5 ja 6
  - artikkeli: theory3, 2 ja 12
  - teoria: theory3, pöytä, 0 ja 0
  - artikkeli: theory3, 7 ja 57
  - theory2 teoria koko 2
  - teoria: theory2, square, 6 ja 8
  - teoria: theory0, linear, 6 ja 9
  - artikkeli: theory3, 8 ja 72
  - artikkeli: theory3, 9 ja 89
  - theory3 teoria koko 10
Tieto:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Säännöt:
  - sääntö teoria tulla häviötön joss se ennakoida jokainen havainnointi täsmälleen
  - sääntö valita häviötön teoria vaille vähin koko
Semantiikka: linear muotoilla y = p1 * x + p2; square muotoilla y = x * x + p2; constant muotoilla y = p2; pöytä muotoilla y = entry(x).
Mikä smallest häviötön teoria?

候选项如下：
  - theory0的理论规模是3
  - theory1的理论规模是2
  - 的条目是：theory3、3和17
  - 的理论是：theory1、square、5和6
  - 的条目是：theory3、2和12
  - 的理论是：theory3、桌子、0和0
  - 的条目是：theory3、7和57
  - theory2的理论规模是2
  - 的理论是：theory2、square、6和8
  - 的理论是：theory0、linear、6和9
  - 的条目是：theory3、8和72
  - 的条目是：theory3、9和89
  - theory3的理论规模是10
数据如下：
  - 3观察到17
  - 8观察到72
  - 9观察到89
  - 2观察到12
  - 7观察到57
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

候補者:
  - theory03理論大きさ
  - theory12理論大きさ
  - 項目:theory3, 3と17
  - 理論:theory1, square, 5と6
  - 項目:theory3, 2と12
  - 理論:theory3, 台, 0と0
  - 項目:theory3, 7と57
  - theory22理論大きさ
  - 理論:theory2, square, 6と8
  - 理論:theory0, linear, 6と9
  - 項目:theory3, 8と72
  - 項目:theory3, 9と89
  - theory310理論大きさ
資料:
  - 317obs
  - 872obs
  - 989obs
  - 212obs
  - 757obs
規則:規則:理論れるロスレスiffこれ予言する凡ゆる観察正確に; 規則:選ぶロスレス理論の中の最小の大きさ.
意味論:lineary = p1 * x + p2形作る; squarey = x * x + p2形作る; constanty = p2形作る; 台y = entry(x)形作る.
smallestロスレス理論何と?

Adaylar:
  - theory0 3 kuram boyut
  - theory1 2 kuram boyut
  - entry: theory3, 3 ve 17
  - kuram: theory1, square, 5 ve 6
  - entry: theory3, 2 ve 12
  - kuram: theory3, masa, 0 ve 0
  - entry: theory3, 7 ve 57
  - theory2 2 kuram boyut
  - kuram: theory2, square, 6 ve 8
  - kuram: theory0, linear, 6 ve 9
  - entry: theory3, 8 ve 72
  - entry: theory3, 9 ve 89
  - theory3 10 kuram boyut
Veriler:
  - 3 17 obs
  - 8 72 obs
  - 9 89 obs
  - 2 12 obs
  - 7 57 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

مُرَشَّح:
  - نَظَرِيَّة مَقَاس theory0 3
  - نَظَرِيَّة مَقَاس theory1 2
  - مَدْخَل: theory3، 3 وَـ 17
  - نَظَرِيَّة: theory1، square، 5 وَـ 6
  - مَدْخَل: theory3، 2 وَـ 12
  - نَظَرِيَّة: theory3، طَاوِلَة، 0 وَـ 0
  - مَدْخَل: theory3، 7 وَـ 57
  - نَظَرِيَّة مَقَاس theory2 2
  - نَظَرِيَّة: theory2، square، 6 وَـ 8
  - نَظَرِيَّة: theory0، linear، 6 وَـ 9
  - مَدْخَل: theory3، 8 وَـ 72
  - مَدْخَل: theory3، 9 وَـ 89
  - نَظَرِيَّة مَقَاس theory3 10
بَيَانَات:
  - obs 3 17
  - obs 8 72
  - obs 9 89
  - obs 2 12
  - obs 7 57
قَانُون:
  - قَانُون نَظَرِيَّة كَانَ lossless iff هُوَ تَنَبَّأَ كُلّ رَصْد بِالضَّبْط
  - قَانُون اِخْتَارَ الـ lossless نَظَرِيَّة مِنْ أَقَلَّ مَقَاس
عِلْم اَلْمَعَانِي: شَكَّلَ linear y = p1 * x + p2؛ شَكَّلَ square y = x * x + p2؛ شَكَّلَ constant y = p2؛ شَكَّلَ الـ طَاوِلَة y = entry(x).
smallest lossless نَظَرِيَّة مَاذَا؟

Კანდიდატები:
  - theory0 3 თეორია ზომა
  - theory1 2 თეორია ზომა
  - სასათაურო სიტყვა: theory3, 3 და 17
  - თეორია: theory1, square, 5 და 6
  - სასათაურო სიტყვა: theory3, 2 და 12
  - თეორია: theory3, მაგიდა, 0 და 0
  - სასათაურო სიტყვა: theory3, 7 და 57
  - theory2 2 თეორია ზომა
  - თეორია: theory2, square, 6 და 8
  - თეორია: theory0, linear, 6 და 9
  - სასათაურო სიტყვა: theory3, 8 და 72
  - სასათაურო სიტყვა: theory3, 9 და 89
  - theory3 10 თეორია ზომა
Მონაცემები:
  - 3 17 obs
  - 8 72 obs
  - 9 89 obs
  - 2 12 obs
  - 7 57 obs
Წესი:
  - წესი თეორია ყოფნა უდანაკარგო iff ის predict ყველა დაკვირვება ზუსტად
  - წესი ამორჩევა უდანაკარგო თეორია of least ზომა
Სემანტიკა: linear y = p1 * x + p2 ბლანკი; square y = x * x + p2 ბლანკი; constant y = p2 ბლანკი; მაგიდა y = entry(x) ბლანკი.
Smallest უდანაკარგო თეორია რა?

Kaiwhakauru:
  - ariā size theory0 3
  - ariā size theory1 2
  - tāurunga: theory3, 3 me 17
  - ariā: theory1, square, 5 me 6
  - tāurunga: theory3, 2 me 12
  - ariā: theory3, tēpu, 0 me 0
  - tāurunga: theory3, 7 me 57
  - ariā size theory2 2
  - ariā: theory2, square, 6 me 8
  - ariā: theory0, linear, 6 me 9
  - tāurunga: theory3, 8 me 72
  - tāurunga: theory3, 9 me 89
  - ariā size theory3 10
Hōtuku:
  - obs 3 17
  - obs 8 72
  - obs 9 89
  - obs 2 12
  - obs 7 57
Rekureihana:
  - rekureihana ariā is lossless iff it matakite every observation pū
  - rekureihana whiri te lossless ariā o least size
Semantics: āhua linear y = p1 * x + p2; āhua square y = x * x + p2; āhua constant y = p2; āhua te tēpu y = entry(x).
Smallest lossless ariā unutai?

Candidates:
  - theory0 lý thuyết kích thước 3
  - theory1 lý thuyết kích thước 2
  - mục từ: theory3, 3 và 17
  - lý thuyết: theory1, square, 5 và 6
  - mục từ: theory3, 2 và 12
  - lý thuyết: theory3, bàn, 0 và 0
  - mục từ: theory3, 7 và 57
  - theory2 lý thuyết kích thước 2
  - lý thuyết: theory2, square, 6 và 8
  - lý thuyết: theory0, linear, 6 và 9
  - mục từ: theory3, 8 và 72
  - mục từ: theory3, 9 và 89
  - theory3 lý thuyết kích thước 10
Dữ liệu:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Quy tắc:
  - quy tắc lý thuyết được lossless iff nó dự báo mỗi observation đúng rồi
  - quy tắc chọn the lossless lý thuyết bằng least kích thước
Ngữ nghĩa: linear làm thành y = p1 * x + p2; square làm thành y = x * x + p2; constant làm thành y = p2; bàn làm thành y = entry(x).
Smallest lossless lý thuyết gì?

ผู้สมัคร:
  - theory0ทฤษฎีขนาด3
  - theory1ทฤษฎีขนาด2
  - entry:theory3, 3และ17
  - ทฤษฎี:theory1, square, 5และ6
  - entry:theory3, 2และ12
  - ทฤษฎี:theory3, โต๊ะ, 0และ0
  - entry:theory3, 7และ57
  - theory2ทฤษฎีขนาด2
  - ทฤษฎี:theory2, square, 6และ8
  - ทฤษฎี:theory0, linear, 6และ9
  - entry:theory3, 8และ72
  - entry:theory3, 9และ89
  - theory3ทฤษฎีขนาด10
ข้อมูล:
  - 3obs17
  - 8obs72
  - 9obs89
  - 2obs12
  - 7obs57
กฎ:กฎ:ทฤษฎีถูกlosslessiffมันทำนายทุกการสังเกตexactly; กฎ:เลือกlosslessทฤษฎีของleastขนาด.
อรรถศาสตร์:linearรูปร่างy = p1 * x + p2; squareรูปร่างy = x * x + p2; constantรูปร่างy = p2; โต๊ะรูปร่างy = entry(x).
smallestlosslessทฤษฎีอะไร?

வேட்பாளர்:
  - theory0 3 theory size
  - theory1 2 theory size
  - உள்நுழைவதற்கு அனுமதி: theory3, 3 மற்றும் 17
  - theory: theory1, square, 5 மற்றும் 6
  - உள்நுழைவதற்கு அனுமதி: theory3, 2 மற்றும் 12
  - theory: theory3, மேசை, 0 மற்றும் 0
  - உள்நுழைவதற்கு அனுமதி: theory3, 7 மற்றும் 57
  - theory2 2 theory size
  - theory: theory2, square, 6 மற்றும் 8
  - theory: theory0, linear, 6 மற்றும் 9
  - உள்நுழைவதற்கு அனுமதி: theory3, 8 மற்றும் 72
  - உள்நுழைவதற்கு அனுமதி: theory3, 9 மற்றும் 89
  - theory3 10 theory size
தரவுகள்:
  - 3 17 obs
  - 8 72 obs
  - 9 89 obs
  - 2 12 obs
  - 7 57 obs
rules: rule theory படு lossless iff it கணி ஒவ்வொரு observation exactly; rule choose lossless theory கொண்ட least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; மேசை y = entry(x) form.
smallest lossless theory என்ன?

Wagombea ni:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 na 17
  - theory: theory1, square, 5 na 6
  - entry: theory3, 2 na 12
  - theory: theory3, meza, 0 na 0
  - entry: theory3, 7 na 57
  - theory2 theory size 2
  - theory: theory2, square, 6 na 8
  - theory: theory0, linear, 6 na 9
  - entry: theory3, 8 na 72
  - entry: theory3, 9 na 89
  - theory3 theory size 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

Candidates:
  - theory0 3 theory size
  - theory1 2 theory size
  - entry: theory3, 3 dóó 17
  - theory: theory1, square, 5 dóó 6
  - entry: theory3, 2 dóó 12
  - theory: theory3, bikááʼ adání, 0 dóó 0
  - entry: theory3, 7 dóó 57
  - theory2 2 theory size
  - theory: theory2, square, 6 dóó 8
  - theory: theory0, linear, 6 dóó 9
  - entry: theory3, 8 dóó 72
  - entry: theory3, 9 dóó 89
  - theory3 10 theory size
Data:
  - 3 17 obs
  - 8 72 obs
  - 9 89 obs
  - 2 12 obs
  - 7 57 obs
Bee hazʼáanii:
  - bee hazʼáanii theory átʼé lossless iff it predict every observation exactly
  - bee hazʼáanii choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; bikááʼ adání y = entry(x) form.
Smallest lossless theory haʼátʼíísh?

Candidates:
  - theory0 3 theory size
  - theory1 2 theory size
  - entry: theory3, 3 aamma 17
  - theory: theory1, square, 5 aamma 6
  - entry: theory3, 2 aamma 12
  - theory: theory3, table, 0 aamma 0
  - entry: theory3, 7 aamma 57
  - theory2 2 theory size
  - theory: theory2, square, 6 aamma 8
  - theory: theory0, linear, 6 aamma 9
  - entry: theory3, 8 aamma 72
  - entry: theory3, 9 aamma 89
  - theory3 10 theory size
Data:
  - 3 17 obs
  - 8 72 obs
  - 9 89 obs
  - 2 12 obs
  - 7 57 obs
Rules: rule theory a lossless iff una predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 blanketti; square y = x * x + p2 blanketti; constant y = p2 blanketti; table y = entry(x) blanketti.
Smallest lossless theory what?

Candidates:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 na 17
  - theory: theory1, square, 5 na 6
  - entry: theory3, 2 na 12
  - theory: theory3, table, 0 na 0
  - entry: theory3, 7 na 57
  - theory2 theory size 2
  - theory: theory2, square, 6 na 8
  - theory: theory0, linear, 6 na 9
  - entry: theory3, 8 na 72
  - entry: theory3, 9 na 89
  - theory3 theory size 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory bilong least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 17
  - theory: theory1, square, 5 6
  - entry: theory3, 2 12
  - theory: theory3, table, 0 0
  - entry: theory3, 7 57
  - theory2 theory size 2
  - theory: theory2, square, 6 8
  - theory: theory0, linear, 6 9
  - entry: theory3, 8 72
  - entry: theory3, 9 89
  - theory3 theory size 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Nikanixi:
  - nikanixi theory is lossless iff it predict every observation exactly
  - nikanixi choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory kwèch?

Candidates:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 а 17
  - theory: theory1, square, 5 а 6
  - entry: theory3, 2 а 12
  - theory: theory3, table, 0 а 0
  - entry: theory3, 7 а 57
  - theory2 theory size 2
  - theory: theory2, square, 6 а 8
  - theory: theory0, linear, 6 а 9
  - entry: theory3, 8 а 72
  - entry: theory3, 9 а 89
  - theory3 theory size 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Rules:
  - rule theory хила lossless iff it predict дерриг observation exactly
  - rule хержа lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory фу?

후보자:
  - theory0 3 이론 크기
  - theory1 2 이론 크기
  - 항목: theory3, 3 17
  - 이론: theory1, square, 5 6
  - 항목: theory3, 2 12
  - 이론: theory3, 테이블, 0 0
  - 항목: theory3, 7 57
  - theory2 2 이론 크기
  - 이론: theory2, square, 6 8
  - 이론: theory0, linear, 6 9
  - 항목: theory3, 8 72
  - 항목: theory3, 9 89
  - theory3 10 이론 크기
자료:
  - 3 17 obs
  - 8 72 obs
  - 9 89 obs
  - 2 12 obs
  - 7 57 obs
규칙: 규칙 이론 is lossless iff 이것 예언하다 각 관찰 정확하게; 규칙 고르다 lossless 이론...의 가장 적게 크기.
의미론: linear y = p1 * x + p2 형상; square y = x * x + p2 형상; constant y = p2 형상; 테이블 y = entry(x) 형상.
smallest lossless 이론 무엇?

Kandidatu:
  - theory0 3 theory tamaina
  - theory1 2 theory tamaina
  - sarrera: theory3, 3 eta 17
  - theory: theory1, square, 5 eta 6
  - sarrera: theory3, 2 eta 12
  - theory: theory3, mahai, 0 eta 0
  - sarrera: theory3, 7 eta 57
  - theory2 2 theory tamaina
  - theory: theory2, square, 6 eta 8
  - theory: theory0, linear, 6 eta 9
  - sarrera: theory3, 8 eta 72
  - sarrera: theory3, 9 eta 89
  - theory3 10 theory tamaina
Data:
  - 3 17 obs
  - 8 72 obs
  - 9 89 obs
  - 2 12 obs
  - 7 57 obs
Arau:
  - arau bat theory izan lossless iff it aurresan every observation exactly
  - arau aukeratu the lossless theory of least tamaina
Semantics: linear y = p1 * x + p2 forma; square y = x * x + p2 forma; constant y = p2 forma; mahai y = entry(x) forma.
Smallest lossless theory zer?

ᎠᏙᎩᏯᏍᎩ:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 ᎠᎴ 17
  - theory: theory1, square, 5 ᎠᎴ 6
  - entry: theory3, 2 ᎠᎴ 12
  - theory: theory3, ᎦᏍᎩᎶ, 0 ᎠᎴ 0
  - entry: theory3, 7 ᎠᎴ 57
  - theory2 theory size 2
  - theory: theory2, square, 6 ᎠᎴ 8
  - theory: theory0, linear, 6 ᎠᎴ 9
  - entry: theory3, 8 ᎠᎴ 72
  - entry: theory3, 9 ᎠᎴ 89
  - theory3 theory size 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ᎦᏍᎩᎶ form y = entry(x).
What smallest lossless theory?

Candidates:
  - theory0 theory chhika 3
  - theory1 theory chhika 2
  - entry: theory3, 3 17
  - theory: theory1, square, 5 6
  - entry: theory3, 2 12
  - theory: theory3, patacha, 0 0
  - entry: theory3, 7 57
  - theory2 theory chhika 2
  - theory: theory2, square, 6 8
  - theory: theory0, linear, 6 9
  - entry: theory3, 8 72
  - entry: theory3, 9 89
  - theory3 theory chhika 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Rules:
  - rule theory tiyay lossless iff it predict tukuy observation exactly
  - rule akllay lossless theory of least chhika
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; patacha form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory0 3 тиориэ size
  - theory1 2 тиориэ size
  - entry: theory3, 3 ыкӏи 17
  - тиориэ: theory1, square, 5 ыкӏи 6
  - entry: theory3, 2 ыкӏи 12
  - тиориэ: theory3, table, 0 ыкӏи 0
  - entry: theory3, 7 ыкӏи 57
  - theory2 2 тиориэ size
  - тиориэ: theory2, square, 6 ыкӏи 8
  - тиориэ: theory0, linear, 6 ыкӏи 9
  - entry: theory3, 8 ыкӏи 72
  - entry: theory3, 9 ыкӏи 89
  - theory3 10 тиориэ size
Data:
  - 3 17 obs
  - 8 72 obs
  - 9 89 obs
  - 2 12 obs
  - 7 57 obs
Rules: rule тиориэ is lossless iff it predict every observation exactly; rule choose the lossless тиориэ of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless тиориэ сыд?

Candidates:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 thiab 17
  - theory: theory1, square, 5 thiab 6
  - entry: theory3, 2 thiab 12
  - theory: theory3, rooj, 0 thiab 0
  - entry: theory3, 7 thiab 57
  - theory2 theory size 2
  - theory: theory2, square, 6 thiab 8
  - theory: theory0, linear, 6 thiab 9
  - entry: theory3, 8 thiab 72
  - entry: theory3, 9 thiab 89
  - theory3 theory size 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Cai: cai theory is lossless iff nws predict every observation exactly; cai choose lossless theory of least size.
Lub ntsiab: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; rooj form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 17
  - theory: theory1, square, 5 6
  - entry: theory3, 2 12
  - theory: theory3, table, 0 0
  - entry: theory3, 7 57
  - theory2 theory size 2
  - theory: theory2, square, 6 8
  - theory: theory0, linear, 6 9
  - entry: theory3, 8 72
  - entry: theory3, 9 89
  - theory3 theory size 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of wy krook size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory ining-jak?

Candidates:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 micha' 17
  - theory: theory1, square, 5 micha' 6
  - entry: theory3, 2 micha' 12
  - theory: theory3, table, 0 micha' 0
  - entry: theory3, 7 micha' 57
  - theory2 theory size 2
  - theory: theory2, square, 6 micha' 8
  - theory: theory0, linear, 6 micha' 9
  - entry: theory3, 8 micha' 72
  - entry: theory3, 9 micha' 89
  - theory3 theory size 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory nanta?

Candidates:
  - theory0 3 theory size
  - theory1 2 theory size
  - entry: theory3, 3 カ 17
  - theory: theory1, square, 5 カ 6
  - entry: theory3, 2 カ 12
  - theory: theory3, table, 0 カ 0
  - entry: theory3, 7 カ 57
  - theory2 2 theory size
  - theory: theory2, square, 6 カ 8
  - theory: theory0, linear, 6 カ 9
  - entry: theory3, 8 カ 72
  - entry: theory3, 9 カ 89
  - theory3 10 theory size
Data:
  - 3 17 obs
  - 8 72 obs
  - 9 89 obs
  - 2 12 obs
  - 7 57 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 ノカ; square y = x * x + p2 ノカ; constant y = p2 ノカ; table y = entry(x) ノカ.
Smallest lossless theory what?

Candidates:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 ынкъам 17
  - theory: theory1, square, 5 ынкъам 6
  - entry: theory3, 2 ынкъам 12
  - theory: theory3, table, 0 ынкъам 0
  - entry: theory3, 7 ынкъам 57
  - theory2 theory size 2
  - theory: theory2, square, 6 ынкъам 8
  - theory: theory0, linear, 6 ынкъам 9
  - entry: theory3, 8 ынкъам 72
  - entry: theory3, 9 ынкъам 89
  - theory3 theory size 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 yéetel 17
  - theory: theory1, square, 5 yéetel 6
  - entry: theory3, 2 yéetel 12
  - theory: theory3, table, 0 yéetel 0
  - entry: theory3, 7 yéetel 57
  - theory2 theory size 2
  - theory: theory2, square, 6 yéetel 8
  - theory: theory0, linear, 6 yéetel 9
  - entry: theory3, 8 yéetel 72
  - entry: theory3, 9 yéetel 89
  - theory3 theory size 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Rules:
  - rule theory yan lossless iff it predict every observation exactly
  - rule yéey lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 17
  - theory: theory1, square, 5 6
  - entry: theory3, 2 12
  - theory: theory3, mę́soną, 0 0
  - entry: theory3, 7 57
  - theory2 theory size 2
  - theory: theory2, square, 6 8
  - theory: theory0, linear, 6 9
  - entry: theory3, 8 72
  - entry: theory3, 9 89
  - theory3 theory size 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Rules:
  - rule theory is lossless iff ą́wąną predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mę́soną form y = entry(x).
Smallest lossless theory híli?

Candidates:
  - theory0 3 theory size
  - theory1 2 theory size
  - entry: theory3, 3 na 17
  - theory: theory1, square, 5 na 6
  - entry: theory3, 2 na 12
  - theory: theory3, table, 0 na 0
  - entry: theory3, 7 na 57
  - theory2 2 theory size
  - theory: theory2, square, 6 na 8
  - theory: theory0, linear, 6 na 9
  - entry: theory3, 8 na 72
  - entry: theory3, 9 na 89
  - theory3 10 theory size
Data:
  - 3 17 obs
  - 8 72 obs
  - 9 89 obs
  - 2 12 obs
  - 7 57 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 17
  - theory: theory1, square, 5 6
  - entry: theory3, 2 12
  - theory: theory3, table, 0 0
  - entry: theory3, 7 57
  - theory2 theory size 2
  - theory: theory2, square, 6 8
  - theory: theory0, linear, 6 9
  - entry: theory3, 8 72
  - entry: theory3, 9 89
  - theory3 theory size 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory0 3 theory size
  - theory1 2 theory size
  - entry: theory3, 3 17
  - theory: theory1, square, 5 6
  - entry: theory3, 2 12
  - theory: theory3, table, 0 0
  - entry: theory3, 7 57
  - theory2 2 theory size
  - theory: theory2, square, 6 8
  - theory: theory0, linear, 6 9
  - entry: theory3, 8 72
  - entry: theory3, 9 89
  - theory3 10 theory size
Data:
  - 3 17 obs
  - 8 72 obs
  - 9 89 obs
  - 2 12 obs
  - 7 57 obs
Rules:
  - rule maya theory is lossless iff it predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory0 theory ʻǁnàhã 3
  - theory1 theory ʻǁnàhã 2
  - entry: theory3, 3 ǂʻá 17
  - theory: theory1, square, 5 ǂʻá 6
  - entry: theory3, 2 ǂʻá 12
  - theory: theory3, table, 0 ǂʻá 0
  - entry: theory3, 7 ǂʻá 57
  - theory2 theory ʻǁnàhã 2
  - theory: theory2, square, 6 ǂʻá 8
  - theory: theory0, linear, 6 ǂʻá 9
  - entry: theory3, 8 ǂʻá 72
  - entry: theory3, 9 ǂʻá 89
  - theory3 theory ʻǁnàhã 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Rules:
  - rule theory ǀîi lossless iff èh predict every observation exactly
  - rule choose lossless theory of least ʻǁnàhã
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory0 3 theory size
  - theory1 2 theory size
  - entry: theory3, 3 17
  - theory: theory1, square, 5 6
  - entry: theory3, 2 12
  - theory: theory3, остол, 0 0
  - entry: theory3, 7 57
  - theory2 2 theory size
  - theory: theory2, square, 6 8
  - theory: theory0, linear, 6 9
  - entry: theory3, 8 72
  - entry: theory3, 9 89
  - theory3 10 theory size
Data:
  - 3 17 obs
  - 8 72 obs
  - 9 89 obs
  - 2 12 obs
  - 7 57 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; остол y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 17
  - theory: theory1, square, 5 6
  - entry: theory3, 2 12
  - theory: theory3, table, 0 0
  - entry: theory3, 7 57
  - theory2 theory size 2
  - theory: theory2, square, 6 8
  - theory: theory0, linear, 6 9
  - entry: theory3, 8 72
  - entry: theory3, 9 89
  - theory3 theory size 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory0 3 theory size
  - theory1 2 theory size
  - entry: theory3, 3 17
  - theory: theory1, square, 5 6
  - entry: theory3, 2 12
  - theory: theory3, table, 0 0
  - entry: theory3, 7 57
  - theory2 2 theory size
  - theory: theory2, square, 6 8
  - theory: theory0, linear, 6 9
  - entry: theory3, 8 72
  - entry: theory3, 9 89
  - theory3 10 theory size
Data:
  - 3 17 obs
  - 8 72 obs
  - 9 89 obs
  - 2 12 obs
  - 7 57 obs
Rules:
  - rule theory is lossless iff kitu predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 17
  - theory: theory1, square, 5 6
  - entry: theory3, 2 12
  - theory: theory3, mesa, 0 0
  - entry: theory3, 7 57
  - theory2 theory size 2
  - theory: theory2, square, 6 8
  - theory: theory0, linear, 6 9
  - entry: theory3, 8 72
  - entry: theory3, 9 89
  - theory3 theory size 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mesa form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 17
  - theory: theory1, square, 5 6
  - entry: theory3, 2 12
  - theory: theory3, table, 0 0
  - entry: theory3, 7 57
  - theory2 theory size 2
  - theory: theory2, square, 6 8
  - theory: theory0, linear, 6 9
  - entry: theory3, 8 72
  - entry: theory3, 9 89
  - theory3 theory size 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Rules:
  - rule theory nemi lossless iff yaja predict every observation exactly
  - rule choose ne lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ne table form y = entry(x).
Smallest lossless theory tay?

Les candidats sont:
  - theory0 théorie taille 3
  - theory1 théorie taille 2
  - article: theory3, 3 et 17
  - théorie: theory1, square, 5 et 6
  - article: theory3, 2 et 12
  - théorie: theory3, table, 0 et 0
  - article: theory3, 7 et 57
  - theory2 théorie taille 2
  - théorie: theory2, square, 6 et 8
  - théorie: theory0, linear, 6 et 9
  - article: theory3, 8 et 72
  - article: theory3, 9 et 89
  - theory3 théorie taille 10
Les données sont:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Les règles sont:
  - règle un théorie être lossless ssi il prédire tout observation exactement
  - règle choisir le lossless théorie du moindre taille
La sémantique est : linear former y = p1 * x + p2 ; square former y = x * x + p2 ; constant former y = p2 ; la table former y = entry(x).
Quoi smallest lossless théorie ?

Kandidato:
  - theory0 teorio grandeco 3
  - theory1 teorio grandeco 2
  - entry: theory3, 3 kaj 17
  - teorio: theory1, square, 5 kaj 6
  - entry: theory3, 2 kaj 12
  - teorio: theory3, tablo, 0 kaj 0
  - entry: theory3, 7 kaj 57
  - theory2 teorio grandeco 2
  - teorio: theory2, square, 6 kaj 8
  - teorio: theory0, linear, 6 kaj 9
  - entry: theory3, 8 kaj 72
  - entry: theory3, 9 kaj 89
  - theory3 teorio grandeco 10
Datumo:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Regulo: regulo teorio egali lossless iff ĝi predict ĉiu observo ekzakte; regulo elekti lossless teorio de plej malmulta grandeco.
Semantics: linear formi y = p1 * x + p2; square formi y = x * x + p2; constant formi y = p2; tablo formi y = entry(x).
Smallest lossless teorio kio?

Indulók:
  - theory0 elmélet méret 3
  - theory1 elmélet méret 2
  - szócikk: theory3, 3 és 17
  - elmélet: theory1, square, 5 és 6
  - szócikk: theory3, 2 és 12
  - elmélet: theory3, asztal, 0 és 0
  - szócikk: theory3, 7 és 57
  - theory2 elmélet méret 2
  - elmélet: theory2, square, 6 és 8
  - elmélet: theory0, linear, 6 és 9
  - szócikk: theory3, 8 és 72
  - szócikk: theory3, 9 és 89
  - theory3 elmélet méret 10
Adat:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Szabályok:
  - szabály elmélet van veszteségmentes acsa az megjósol minden megfigyelés pontosan
  - szabály kiválaszt a veszteségmentes elmélet of legkisebb méret
Szemantika: linear kialakít y = p1 * x + p2; square kialakít y = x * x + p2; constant kialakít y = p2; a asztal kialakít y = entry(x).
Smallest veszteségmentes elmélet melyik?

候選人:
  - theory0theory size3
  - theory1theory size2
  - entry:theory3, 3及17
  - theory:theory1, square, 5及6
  - entry:theory3, 2及12
  - theory:theory3, 檯, 0及0
  - entry:theory3, 7及57
  - theory2theory size2
  - theory:theory2, square, 6及8
  - theory:theory0, linear, 6及9
  - entry:theory3, 8及72
  - entry:theory3, 9及89
  - theory3theory size10
數據:
  - 3obs17
  - 8obs72
  - 9obs89
  - 2obs12
  - 7obs57
rules:rule:一theory是losslessiffitpredict每observationexactly; rule:揀losslesstheory...嘅leastsize.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; 檯formy = entry(x).
smallest lossless theory乜嘢?

Candidates:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 とぅ 17
  - theory: theory1, square, 5 とぅ 6
  - entry: theory3, 2 とぅ 12
  - theory: theory3, table, 0 とぅ 0
  - entry: theory3, 7 とぅ 57
  - theory2 theory size 2
  - theory: theory2, square, 6 とぅ 8
  - theory: theory0, linear, 6 とぅ 9
  - entry: theory3, 8 とぅ 72
  - entry: theory3, 9 とぅ 89
  - theory3 theory size 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Rules: rule theory 有ん lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Үміткер:
  - theory0 теория мөлшер 3
  - theory1 теория мөлшер 2
  - entry: theory3, 3 және 17
  - теория: theory1, square, 5 және 6
  - entry: theory3, 2 және 12
  - теория: theory3, үстел, 0 және 0
  - entry: theory3, 7 және 57
  - theory2 теория мөлшер 2
  - теория: theory2, square, 6 және 8
  - теория: theory0, linear, 6 және 9
  - entry: theory3, 8 және 72
  - entry: theory3, 9 және 89
  - theory3 теория мөлшер 10
Деректер:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Ереже: ереже теория is lossless iff ол predict әр бақылау exactly; ереже таңдау lossless теория туралы least мөлшер.
Семантикалық: linear пішін y = p1 * x + p2; square пішін y = x * x + p2; constant пішін y = p2; үстел пішін y = entry(x).
Smallest lossless теория не?

מועמדת:
  - theory0 תּוֹרָה גֹּדֶל 3
  - theory1 תּוֹרָה גֹּדֶל 2
  - entry: theory3, 3 וְ־ 17
  - תּוֹרָה: theory1, square, 5 וְ־ 6
  - entry: theory3, 2 וְ־ 12
  - תּוֹרָה: theory3, טַבְלָה, 0 וְ־ 0
  - entry: theory3, 7 וְ־ 57
  - theory2 תּוֹרָה גֹּדֶל 2
  - תּוֹרָה: theory2, square, 6 וְ־ 8
  - תּוֹרָה: theory0, linear, 6 וְ־ 9
  - entry: theory3, 8 וְ־ 72
  - entry: theory3, 9 וְ־ 89
  - theory3 תּוֹרָה גֹּדֶל 10
נְתוּנִים:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
מָשַׁל:
  - מָשַׁל אַחַת תּוֹרָה הוא lossless אםם זֶה predict כֹּל תַּצְפִּית בדיוק
  - מָשַׁל בחר ה־ lossless תּוֹרָה שֶׁל least גֹּדֶל
תורת המשמעים: linear צורה y = p1 * x + p2; square צורה y = x * x + p2; constant צורה y = p2; טַבְלָה ה־ צורה y = entry(x).
איזה smallest lossless תּוֹרָה?

Candidates:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 დო 17
  - theory: theory1, square, 5 დო 6
  - entry: theory3, 2 დო 12
  - theory: theory3, table, 0 დო 0
  - entry: theory3, 7 დო 57
  - theory2 theory size 2
  - theory: theory2, square, 6 დო 8
  - theory: theory0, linear, 6 დო 9
  - entry: theory3, 8 დო 72
  - entry: theory3, 9 დო 89
  - theory3 theory size 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Kandidat:
  - theory0 teori ukuran 3
  - theory1 teori ukuran 2
  - lema: theory3, 3 dan 17
  - teori: theory1, square, 5 dan 6
  - lema: theory3, 2 dan 12
  - teori: theory3, meja, 0 dan 0
  - lema: theory3, 7 dan 57
  - theory2 teori ukuran 2
  - teori: theory2, square, 6 dan 8
  - teori: theory0, linear, 6 dan 9
  - lema: theory3, 8 dan 72
  - lema: theory3, 9 dan 89
  - theory3 teori ukuran 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Rules:
  - rule teori berada lossless iff it predict setiap observation tepat
  - rule memilih si lossless teori dari least ukuran
Semantik: linear formulir y = p1 * x + p2; square formulir y = x * x + p2; constant formulir y = p2; meja si formulir y = entry(x).
Smallest lossless teori apa?

បេក្ខជន:
  - theory0ទ្រឹស្ដីទំហំ3
  - theory1ទ្រឹស្ដីទំហំ2
  - មេពាក្យ:theory3, 3នឹង17
  - ទ្រឹស្ដី:theory1, square, 5នឹង6
  - មេពាក្យ:theory3, 2នឹង12
  - ទ្រឹស្ដី:theory3, តុ, 0នឹង0
  - មេពាក្យ:theory3, 7នឹង57
  - theory2ទ្រឹស្ដីទំហំ2
  - ទ្រឹស្ដី:theory2, square, 6នឹង8
  - ទ្រឹស្ដី:theory0, linear, 6នឹង9
  - មេពាក្យ:theory3, 8នឹង72
  - មេពាក្យ:theory3, 9នឹង89
  - theory3ទ្រឹស្ដីទំហំ10
ទិន្នន័យ:
  - 3obs17
  - 8obs72
  - 9obs89
  - 2obs12
  - 7obs57
ក្បួន:ក្បួន:ទ្រឹស្ដីត្រូវបានlosslessiffវាចាប់យាមរាល់គំនន់exactly; ក្បួន:រើសthelosslessទ្រឹស្ដីនៃleastទំហំ.
និឃណ្ដសាស្ត្រ:linearគ្រោងy = p1 * x + p2; squareគ្រោងy = x * x + p2; constantគ្រោងy = p2; តុគ្រោងy = entry(x).
smallestlosslessទ្រឹស្ដីអី?

ຜູ້ສະໝັກ:
  - theory0ທິດສະດີຂະຫນາດ3
  - theory1ທິດສະດີຂະຫນາດ2
  - entry:theory3, 3ແລະ17
  - ທິດສະດີ:theory1, square, 5ແລະ6
  - entry:theory3, 2ແລະ12
  - ທິດສະດີ:theory3, ໂຕະ, 0ແລະ0
  - entry:theory3, 7ແລະ57
  - theory2ທິດສະດີຂະຫນາດ2
  - ທິດສະດີ:theory2, square, 6ແລະ8
  - ທິດສະດີ:theory0, linear, 6ແລະ9
  - entry:theory3, 8ແລະ72
  - entry:theory3, 9ແລະ89
  - theory3ທິດສະດີຂະຫນາດ10
ຂໍ້ມູນ:
  - 3obs17
  - 8obs72
  - 9obs89
  - 2obs12
  - 7obs57
ກະຕິກາ:ກະຕິກາ:ທິດສະດີຢູ່losslessiffມັນທຳນວາຍທຸກobservationexactly; ກະຕິກາ:ເລືອກlosslessທິດສະດີຂອງleastຂະຫນາດ.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; ໂຕະformy = entry(x).
smallestlosslessທິດສະດີຫຍັງ?

candidates:
  - theory0 3 theory size
  - theory1 2 theory size
  - entry: theory3, 3 మరియు 17
  - theory: theory1, square, 5 మరియు 6
  - entry: theory3, 2 మరియు 12
  - theory: theory3, బల్ల, 0 మరియు 0
  - entry: theory3, 7 మరియు 57
  - theory2 2 theory size
  - theory: theory2, square, 6 మరియు 8
  - theory: theory0, linear, 6 మరియు 9
  - entry: theory3, 8 మరియు 72
  - entry: theory3, 9 మరియు 89
  - theory3 10 theory size
data:
  - 3 17 obs
  - 8 72 obs
  - 9 89 obs
  - 2 12 obs
  - 7 57 obs
నియమం: నియమం theory ఉండు lossless iff it predict ప్రతి పరిశీలన exactly; నియమం choose lossless theory of least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; బల్ల y = entry(x) form.
smallest lossless theory ఏమిటి?

Candidates:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 17
  - theory: theory1, square, 5 6
  - entry: theory3, 2 12
  - theory: theory3, table, 0 0
  - entry: theory3, 7 57
  - theory2 theory size 2
  - theory: theory2, square, 6 8
  - theory: theory0, linear, 6 9
  - entry: theory3, 8 72
  - entry: theory3, 9 89
  - theory3 theory size 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Rules: rule theory wà lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
What smallest lossless theory?

Candidates:
  - theory0 3 theory size
  - theory1 2 theory size
  - entry: theory3, 3 17
  - theory: theory1, square, 5 6
  - entry: theory3, 2 12
  - theory: theory3, table, 0 0
  - entry: theory3, 7 57
  - theory2 2 theory size
  - theory: theory2, square, 6 8
  - theory: theory0, linear, 6 9
  - entry: theory3, 8 72
  - entry: theory3, 9 89
  - theory3 10 theory size
Data:
  - 3 17 obs
  - 8 72 obs
  - 9 89 obs
  - 2 12 obs
  - 7 57 obs
Rules:
  - rule theory naiágúóli lossless iff it predict every observation exactly
  - rule choose the lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

candidates:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 17
  - theory: theory1, square, 5 6
  - entry: theory3, 2 12
  - theory: theory3, table, 0 0
  - entry: theory3, 7 57
  - theory2 theory size 2
  - theory: theory2, square, 6 8
  - theory: theory0, linear, 6 9
  - entry: theory3, 8 72
  - entry: theory3, 9 89
  - theory3 theory size 10
data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
smallest lossless theory what?

Candidates:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 17
  - theory: theory1, square, 5 6
  - entry: theory3, 2 12
  - theory: theory3, tafra, 0 0
  - entry: theory3, 7 57
  - theory2 theory size 2
  - theory: theory2, square, 6 8
  - theory: theory0, linear, 6 9
  - entry: theory3, 8 72
  - entry: theory3, 9 89
  - theory3 theory size 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; tafra form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory0 theory size 3
  - theory1 theory size 2
  - entry: theory3, 3 17
  - theory: theory1, square, 5 6
  - entry: theory3, 2 12
  - theory: theory3, táxemésėhestȯtse, 0 0
  - entry: theory3, 7 57
  - theory2 theory size 2
  - theory: theory2, square, 6 8
  - theory: theory0, linear, 6 9
  - entry: theory3, 8 72
  - entry: theory3, 9 89
  - theory3 theory size 10
Data:
  - 3 obs 17
  - 8 obs 72
  - 9 obs 89
  - 2 obs 12
  - 7 obs 57
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; táxemésėhestȯtse form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory0 3 theory size
  - theory1 2 theory size
  - entry: theory3, 3 17
  - theory: theory1, square, 5 6
  - entry: theory3, 2 12
  - theory: theory3, ствал, 0 0
  - entry: theory3, 7 57
  - theory2 2 theory size
  - theory: theory2, square, 6 8
  - theory: theory0, linear, 6 9
  - entry: theory3, 8 72
  - entry: theory3, 9 89
  - theory3 10 theory size
Data:
  - 3 17 obs
  - 8 72 obs
  - 9 89 obs
  - 2 12 obs
  - 7 57 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; ствал y = entry(x) form.
Smallest lossless theory вуч?

The candidates are:
  - entry: theory1, 0 and 5
  - entry: theory1, 5 and 30
  - theory: theory2, linear, 4 and 8
  - theory: theory3, square, 3 and 3
  - entry: theory1, 7 and 54
  - theory: theory0, square, 4 and 5
  - theory1 theory size 10
  - theory: theory1, table, 0 and 0
  - theory3 theory size 2
  - entry: theory1, 2 and 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 and 41
The data are:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

Los candidatos son:
  - la entrada: theory1, 0 y 5
  - la entrada: theory1, 5 y 30
  - la teoría: theory2, linear, 4 y 8
  - la teoría: theory3, square, 3 y 3
  - la entrada: theory1, 7 y 54
  - la teoría: theory0, square, 4 y 5
  - theory1 el tamaño de la teoría 10
  - la teoría: theory1, mesa, 0 y 0
  - theory3 el tamaño de la teoría 2
  - la entrada: theory1, 2 y 9
  - theory0 el tamaño de la teoría 2
  - theory2 el tamaño de la teoría 3
  - la entrada: theory1, 6 y 41
Los datos son:
  - 7 la observación 54
  - 5 la observación 30
  - 2 la observación 9
  - 0 la observación 5
  - 6 la observación 41
Las reglas son:
  - la regla: a la teoría es lossless si y sólo si it predice every observation exactamente
  - la regla: choose el lossless la teoría de least tamaño
La semántica es: linear la forma y = p1 * x + p2; square la forma y = x * x + p2; constant la forma y = p2; la mesa la forma y = entry(x).
¿Qué smallest lossless la teoría?

候选项如下：
  - 的条目是：theory1、0和5
  - 的条目是：theory1、5和30
  - 的理论是：theory2、linear、4和8
  - 的理论是：theory3、square、3和3
  - 的条目是：theory1、7和54
  - 的理论是：theory0、square、4和5
  - theory1的理论规模是10
  - 的理论是：theory1、桌子、0和0
  - theory3的理论规模是2
  - 的条目是：theory1、2和9
  - theory0的理论规模是2
  - theory2的理论规模是3
  - 的条目是：theory1、6和41
数据如下：
  - 7观察到54
  - 5观察到30
  - 2观察到9
  - 0观察到5
  - 6观察到41
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

Adaylar:
  - entry: theory1, 0 ve 5
  - entry: theory1, 5 ve 30
  - kuram: theory2, linear, 4 ve 8
  - kuram: theory3, square, 3 ve 3
  - entry: theory1, 7 ve 54
  - kuram: theory0, square, 4 ve 5
  - theory1 10 kuram boyut
  - kuram: theory1, masa, 0 ve 0
  - theory3 2 kuram boyut
  - entry: theory1, 2 ve 9
  - theory0 2 kuram boyut
  - theory2 3 kuram boyut
  - entry: theory1, 6 ve 41
Veriler:
  - 7 54 obs
  - 5 30 obs
  - 2 9 obs
  - 0 5 obs
  - 6 41 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

Wagombea ni:
  - entry: theory1, 0 na 5
  - entry: theory1, 5 na 30
  - theory: theory2, linear, 4 na 8
  - theory: theory3, square, 3 na 3
  - entry: theory1, 7 na 54
  - theory: theory0, square, 4 na 5
  - theory1 theory size 10
  - theory: theory1, meza, 0 na 0
  - theory3 theory size 2
  - entry: theory1, 2 na 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 na 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

The candidates are:
  - entry: theory1, 0 and 5
  - entry: theory1, 5 and 30
  - theory: theory2, linear, 4 and 8
  - theory: theory3, square, 3 and 3
  - entry: theory1, 7 and 54
  - theory: theory0, square, 4 and 5
  - theory1 theory size 10
  - theory: theory1, table, 0 and 0
  - theory3 theory size 2
  - entry: theory1, 2 and 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 and 41
The data are:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

{candidates: [(entry theory1 0 5) (entry theory1 5 30) (theory theory2 linear 4 8) (theory theory3 square 3 3) (entry theory1 7 54) (theory theory0 square 4 5) (theory_size theory1 10) (theory theory1 table 0 0) (theory_size theory3 2) (entry theory1 2 9) (theory_size theory0 2) (theory_size theory2 3) (entry theory1 6 41)], data: [(obs 7 54) (obs 5 30) (obs 2 9) (obs 0 5) (obs 6 41)], query: smallest_lossless_theory, rules: [(rule (a_theory_is_lossless_iff_it_predicts_every_observation_exactly)) (rule (choose_the_lossless_theory_of_least_size))], semantics: [(form linear "y = p1 * x + p2") (form square "y = x * x + p2") (form constant "y = p2") (form table "y = entry(x)")]}

Die Kandidaten sind:
  - Eintrag: theory1, 0 und 5
  - Eintrag: theory1, 5 und 30
  - Theorie: theory2, linear, 4 und 8
  - Theorie: theory3, square, 3 und 3
  - Eintrag: theory1, 7 und 54
  - Theorie: theory0, square, 4 und 5
  - theory1 Theorie Größe 10
  - Theorie: theory1, Tisch, 0 und 0
  - theory3 Theorie Größe 2
  - Eintrag: theory1, 2 und 9
  - theory0 Theorie Größe 2
  - theory2 Theorie Größe 3
  - Eintrag: theory1, 6 und 41
Die Daten sind:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Die Regeln sind:
  - Regel ein Theorie werden verlustfrei gdw. er vorhersagen jeder Beobachtung genau
  - Regel wählen der verlustfrei Theorie aus geringst Größe
Die Semantik ist: linear formen y = p1 * x + p2; square formen y = x * x + p2; constant formen y = p2; der Tisch formen y = entry(x).
Was smallest verlustfrei Theorie?

Кандѝда̄т:
  - одредница: theory1, 0 и 5
  - одредница: theory1, 5 и 30
  - тѐо̄рија: theory2, linear, 4 и 8
  - тѐо̄рија: theory3, square, 3 и 3
  - одредница: theory1, 7 и 54
  - тѐо̄рија: theory0, square, 4 и 5
  - theory1 тѐо̄рија величѝна 10
  - тѐо̄рија: theory1, сто̑л, 0 и 0
  - theory3 тѐо̄рија величѝна 2
  - одредница: theory1, 2 и 9
  - theory0 тѐо̄рија величѝна 2
  - theory2 тѐо̄рија величѝна 3
  - одредница: theory1, 6 и 41
Податци:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Пра̏вило:
  - пра̏вило тѐо̄рија би̏ти lossless iff оно predvidjeti сва̏кӣ опа́жа̄ње тачно
  - пра̏вило изабрати lossless тѐо̄рија od minimalan величѝна
Сема̀нтика: linear oblik y = p1 * x + p2; square oblik y = x * x + p2; constant oblik y = p2; сто̑л oblik y = entry(x).
Smallest lossless тѐо̄рија kakav?

Ehdokkaat:
  - artikkeli: theory1, 0 ja 5
  - artikkeli: theory1, 5 ja 30
  - teoria: theory2, linear, 4 ja 8
  - teoria: theory3, square, 3 ja 3
  - artikkeli: theory1, 7 ja 54
  - teoria: theory0, square, 4 ja 5
  - theory1 teoria koko 10
  - teoria: theory1, pöytä, 0 ja 0
  - theory3 teoria koko 2
  - artikkeli: theory1, 2 ja 9
  - theory0 teoria koko 2
  - theory2 teoria koko 3
  - artikkeli: theory1, 6 ja 41
Tieto:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Säännöt:
  - sääntö teoria tulla häviötön joss se ennakoida jokainen havainnointi täsmälleen
  - sääntö valita häviötön teoria vaille vähin koko
Semantiikka: linear muotoilla y = p1 * x + p2; square muotoilla y = x * x + p2; constant muotoilla y = p2; pöytä muotoilla y = entry(x).
Mikä smallest häviötön teoria?

候选项如下：
  - 的条目是：theory1、0和5
  - 的条目是：theory1、5和30
  - 的理论是：theory2、linear、4和8
  - 的理论是：theory3、square、3和3
  - 的条目是：theory1、7和54
  - 的理论是：theory0、square、4和5
  - theory1的理论规模是10
  - 的理论是：theory1、桌子、0和0
  - theory3的理论规模是2
  - 的条目是：theory1、2和9
  - theory0的理论规模是2
  - theory2的理论规模是3
  - 的条目是：theory1、6和41
数据如下：
  - 7观察到54
  - 5观察到30
  - 2观察到9
  - 0观察到5
  - 6观察到41
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

候補者:
  - 項目:theory1, 0と5
  - 項目:theory1, 5と30
  - 理論:theory2, linear, 4と8
  - 理論:theory3, square, 3と3
  - 項目:theory1, 7と54
  - 理論:theory0, square, 4と5
  - theory110理論大きさ
  - 理論:theory1, 台, 0と0
  - theory32理論大きさ
  - 項目:theory1, 2と9
  - theory02理論大きさ
  - theory23理論大きさ
  - 項目:theory1, 6と41
資料:
  - 754obs
  - 530obs
  - 29obs
  - 05obs
  - 641obs
規則:規則:理論れるロスレスiffこれ予言する凡ゆる観察正確に; 規則:選ぶロスレス理論の中の最小の大きさ.
意味論:lineary = p1 * x + p2形作る; squarey = x * x + p2形作る; constanty = p2形作る; 台y = entry(x)形作る.
smallestロスレス理論何と?

Adaylar:
  - entry: theory1, 0 ve 5
  - entry: theory1, 5 ve 30
  - kuram: theory2, linear, 4 ve 8
  - kuram: theory3, square, 3 ve 3
  - entry: theory1, 7 ve 54
  - kuram: theory0, square, 4 ve 5
  - theory1 10 kuram boyut
  - kuram: theory1, masa, 0 ve 0
  - theory3 2 kuram boyut
  - entry: theory1, 2 ve 9
  - theory0 2 kuram boyut
  - theory2 3 kuram boyut
  - entry: theory1, 6 ve 41
Veriler:
  - 7 54 obs
  - 5 30 obs
  - 2 9 obs
  - 0 5 obs
  - 6 41 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

مُرَشَّح:
  - مَدْخَل: theory1، 0 وَـ 5
  - مَدْخَل: theory1، 5 وَـ 30
  - نَظَرِيَّة: theory2، linear، 4 وَـ 8
  - نَظَرِيَّة: theory3، square، 3 وَـ 3
  - مَدْخَل: theory1، 7 وَـ 54
  - نَظَرِيَّة: theory0، square، 4 وَـ 5
  - نَظَرِيَّة مَقَاس theory1 10
  - نَظَرِيَّة: theory1، طَاوِلَة، 0 وَـ 0
  - نَظَرِيَّة مَقَاس theory3 2
  - مَدْخَل: theory1، 2 وَـ 9
  - نَظَرِيَّة مَقَاس theory0 2
  - نَظَرِيَّة مَقَاس theory2 3
  - مَدْخَل: theory1، 6 وَـ 41
بَيَانَات:
  - obs 7 54
  - obs 5 30
  - obs 2 9
  - obs 0 5
  - obs 6 41
قَانُون:
  - قَانُون نَظَرِيَّة كَانَ lossless iff هُوَ تَنَبَّأَ كُلّ رَصْد بِالضَّبْط
  - قَانُون اِخْتَارَ الـ lossless نَظَرِيَّة مِنْ أَقَلَّ مَقَاس
عِلْم اَلْمَعَانِي: شَكَّلَ linear y = p1 * x + p2؛ شَكَّلَ square y = x * x + p2؛ شَكَّلَ constant y = p2؛ شَكَّلَ الـ طَاوِلَة y = entry(x).
smallest lossless نَظَرِيَّة مَاذَا؟

Კანდიდატები:
  - სასათაურო სიტყვა: theory1, 0 და 5
  - სასათაურო სიტყვა: theory1, 5 და 30
  - თეორია: theory2, linear, 4 და 8
  - თეორია: theory3, square, 3 და 3
  - სასათაურო სიტყვა: theory1, 7 და 54
  - თეორია: theory0, square, 4 და 5
  - theory1 10 თეორია ზომა
  - თეორია: theory1, მაგიდა, 0 და 0
  - theory3 2 თეორია ზომა
  - სასათაურო სიტყვა: theory1, 2 და 9
  - theory0 2 თეორია ზომა
  - theory2 3 თეორია ზომა
  - სასათაურო სიტყვა: theory1, 6 და 41
Მონაცემები:
  - 7 54 obs
  - 5 30 obs
  - 2 9 obs
  - 0 5 obs
  - 6 41 obs
Წესი:
  - წესი თეორია ყოფნა უდანაკარგო iff ის predict ყველა დაკვირვება ზუსტად
  - წესი ამორჩევა უდანაკარგო თეორია of least ზომა
Სემანტიკა: linear y = p1 * x + p2 ბლანკი; square y = x * x + p2 ბლანკი; constant y = p2 ბლანკი; მაგიდა y = entry(x) ბლანკი.
Smallest უდანაკარგო თეორია რა?

Kaiwhakauru:
  - tāurunga: theory1, 0 me 5
  - tāurunga: theory1, 5 me 30
  - ariā: theory2, linear, 4 me 8
  - ariā: theory3, square, 3 me 3
  - tāurunga: theory1, 7 me 54
  - ariā: theory0, square, 4 me 5
  - ariā size theory1 10
  - ariā: theory1, tēpu, 0 me 0
  - ariā size theory3 2
  - tāurunga: theory1, 2 me 9
  - ariā size theory0 2
  - ariā size theory2 3
  - tāurunga: theory1, 6 me 41
Hōtuku:
  - obs 7 54
  - obs 5 30
  - obs 2 9
  - obs 0 5
  - obs 6 41
Rekureihana:
  - rekureihana ariā is lossless iff it matakite every observation pū
  - rekureihana whiri te lossless ariā o least size
Semantics: āhua linear y = p1 * x + p2; āhua square y = x * x + p2; āhua constant y = p2; āhua te tēpu y = entry(x).
Smallest lossless ariā unutai?

Candidates:
  - mục từ: theory1, 0 và 5
  - mục từ: theory1, 5 và 30
  - lý thuyết: theory2, linear, 4 và 8
  - lý thuyết: theory3, square, 3 và 3
  - mục từ: theory1, 7 và 54
  - lý thuyết: theory0, square, 4 và 5
  - theory1 lý thuyết kích thước 10
  - lý thuyết: theory1, bàn, 0 và 0
  - theory3 lý thuyết kích thước 2
  - mục từ: theory1, 2 và 9
  - theory0 lý thuyết kích thước 2
  - theory2 lý thuyết kích thước 3
  - mục từ: theory1, 6 và 41
Dữ liệu:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Quy tắc:
  - quy tắc lý thuyết được lossless iff nó dự báo mỗi observation đúng rồi
  - quy tắc chọn the lossless lý thuyết bằng least kích thước
Ngữ nghĩa: linear làm thành y = p1 * x + p2; square làm thành y = x * x + p2; constant làm thành y = p2; bàn làm thành y = entry(x).
Smallest lossless lý thuyết gì?

ผู้สมัคร:
  - entry:theory1, 0และ5
  - entry:theory1, 5และ30
  - ทฤษฎี:theory2, linear, 4และ8
  - ทฤษฎี:theory3, square, 3และ3
  - entry:theory1, 7และ54
  - ทฤษฎี:theory0, square, 4และ5
  - theory1ทฤษฎีขนาด10
  - ทฤษฎี:theory1, โต๊ะ, 0และ0
  - theory3ทฤษฎีขนาด2
  - entry:theory1, 2และ9
  - theory0ทฤษฎีขนาด2
  - theory2ทฤษฎีขนาด3
  - entry:theory1, 6และ41
ข้อมูล:
  - 7obs54
  - 5obs30
  - 2obs9
  - 0obs5
  - 6obs41
กฎ:กฎ:ทฤษฎีถูกlosslessiffมันทำนายทุกการสังเกตexactly; กฎ:เลือกlosslessทฤษฎีของleastขนาด.
อรรถศาสตร์:linearรูปร่างy = p1 * x + p2; squareรูปร่างy = x * x + p2; constantรูปร่างy = p2; โต๊ะรูปร่างy = entry(x).
smallestlosslessทฤษฎีอะไร?

வேட்பாளர்:
  - உள்நுழைவதற்கு அனுமதி: theory1, 0 மற்றும் 5
  - உள்நுழைவதற்கு அனுமதி: theory1, 5 மற்றும் 30
  - theory: theory2, linear, 4 மற்றும் 8
  - theory: theory3, square, 3 மற்றும் 3
  - உள்நுழைவதற்கு அனுமதி: theory1, 7 மற்றும் 54
  - theory: theory0, square, 4 மற்றும் 5
  - theory1 10 theory size
  - theory: theory1, மேசை, 0 மற்றும் 0
  - theory3 2 theory size
  - உள்நுழைவதற்கு அனுமதி: theory1, 2 மற்றும் 9
  - theory0 2 theory size
  - theory2 3 theory size
  - உள்நுழைவதற்கு அனுமதி: theory1, 6 மற்றும் 41
தரவுகள்:
  - 7 54 obs
  - 5 30 obs
  - 2 9 obs
  - 0 5 obs
  - 6 41 obs
rules: rule theory படு lossless iff it கணி ஒவ்வொரு observation exactly; rule choose lossless theory கொண்ட least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; மேசை y = entry(x) form.
smallest lossless theory என்ன?

Wagombea ni:
  - entry: theory1, 0 na 5
  - entry: theory1, 5 na 30
  - theory: theory2, linear, 4 na 8
  - theory: theory3, square, 3 na 3
  - entry: theory1, 7 na 54
  - theory: theory0, square, 4 na 5
  - theory1 theory size 10
  - theory: theory1, meza, 0 na 0
  - theory3 theory size 2
  - entry: theory1, 2 na 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 na 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

Candidates:
  - entry: theory1, 0 dóó 5
  - entry: theory1, 5 dóó 30
  - theory: theory2, linear, 4 dóó 8
  - theory: theory3, square, 3 dóó 3
  - entry: theory1, 7 dóó 54
  - theory: theory0, square, 4 dóó 5
  - theory1 10 theory size
  - theory: theory1, bikááʼ adání, 0 dóó 0
  - theory3 2 theory size
  - entry: theory1, 2 dóó 9
  - theory0 2 theory size
  - theory2 3 theory size
  - entry: theory1, 6 dóó 41
Data:
  - 7 54 obs
  - 5 30 obs
  - 2 9 obs
  - 0 5 obs
  - 6 41 obs
Bee hazʼáanii:
  - bee hazʼáanii theory átʼé lossless iff it predict every observation exactly
  - bee hazʼáanii choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; bikááʼ adání y = entry(x) form.
Smallest lossless theory haʼátʼíísh?

Candidates:
  - entry: theory1, 0 aamma 5
  - entry: theory1, 5 aamma 30
  - theory: theory2, linear, 4 aamma 8
  - theory: theory3, square, 3 aamma 3
  - entry: theory1, 7 aamma 54
  - theory: theory0, square, 4 aamma 5
  - theory1 10 theory size
  - theory: theory1, table, 0 aamma 0
  - theory3 2 theory size
  - entry: theory1, 2 aamma 9
  - theory0 2 theory size
  - theory2 3 theory size
  - entry: theory1, 6 aamma 41
Data:
  - 7 54 obs
  - 5 30 obs
  - 2 9 obs
  - 0 5 obs
  - 6 41 obs
Rules: rule theory a lossless iff una predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 blanketti; square y = x * x + p2 blanketti; constant y = p2 blanketti; table y = entry(x) blanketti.
Smallest lossless theory what?

Candidates:
  - entry: theory1, 0 na 5
  - entry: theory1, 5 na 30
  - theory: theory2, linear, 4 na 8
  - theory: theory3, square, 3 na 3
  - entry: theory1, 7 na 54
  - theory: theory0, square, 4 na 5
  - theory1 theory size 10
  - theory: theory1, table, 0 na 0
  - theory3 theory size 2
  - entry: theory1, 2 na 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 na 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory bilong least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory1, 0 5
  - entry: theory1, 5 30
  - theory: theory2, linear, 4 8
  - theory: theory3, square, 3 3
  - entry: theory1, 7 54
  - theory: theory0, square, 4 5
  - theory1 theory size 10
  - theory: theory1, table, 0 0
  - theory3 theory size 2
  - entry: theory1, 2 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Nikanixi:
  - nikanixi theory is lossless iff it predict every observation exactly
  - nikanixi choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory kwèch?

Candidates:
  - entry: theory1, 0 а 5
  - entry: theory1, 5 а 30
  - theory: theory2, linear, 4 а 8
  - theory: theory3, square, 3 а 3
  - entry: theory1, 7 а 54
  - theory: theory0, square, 4 а 5
  - theory1 theory size 10
  - theory: theory1, table, 0 а 0
  - theory3 theory size 2
  - entry: theory1, 2 а 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 а 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Rules:
  - rule theory хила lossless iff it predict дерриг observation exactly
  - rule хержа lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory фу?

후보자:
  - 항목: theory1, 0 5
  - 항목: theory1, 5 30
  - 이론: theory2, linear, 4 8
  - 이론: theory3, square, 3 3
  - 항목: theory1, 7 54
  - 이론: theory0, square, 4 5
  - theory1 10 이론 크기
  - 이론: theory1, 테이블, 0 0
  - theory3 2 이론 크기
  - 항목: theory1, 2 9
  - theory0 2 이론 크기
  - theory2 3 이론 크기
  - 항목: theory1, 6 41
자료:
  - 7 54 obs
  - 5 30 obs
  - 2 9 obs
  - 0 5 obs
  - 6 41 obs
규칙: 규칙 이론 is lossless iff 이것 예언하다 각 관찰 정확하게; 규칙 고르다 lossless 이론...의 가장 적게 크기.
의미론: linear y = p1 * x + p2 형상; square y = x * x + p2 형상; constant y = p2 형상; 테이블 y = entry(x) 형상.
smallest lossless 이론 무엇?

Kandidatu:
  - sarrera: theory1, 0 eta 5
  - sarrera: theory1, 5 eta 30
  - theory: theory2, linear, 4 eta 8
  - theory: theory3, square, 3 eta 3
  - sarrera: theory1, 7 eta 54
  - theory: theory0, square, 4 eta 5
  - theory1 10 theory tamaina
  - theory: theory1, mahai, 0 eta 0
  - theory3 2 theory tamaina
  - sarrera: theory1, 2 eta 9
  - theory0 2 theory tamaina
  - theory2 3 theory tamaina
  - sarrera: theory1, 6 eta 41
Data:
  - 7 54 obs
  - 5 30 obs
  - 2 9 obs
  - 0 5 obs
  - 6 41 obs
Arau:
  - arau bat theory izan lossless iff it aurresan every observation exactly
  - arau aukeratu the lossless theory of least tamaina
Semantics: linear y = p1 * x + p2 forma; square y = x * x + p2 forma; constant y = p2 forma; mahai y = entry(x) forma.
Smallest lossless theory zer?

ᎠᏙᎩᏯᏍᎩ:
  - entry: theory1, 0 ᎠᎴ 5
  - entry: theory1, 5 ᎠᎴ 30
  - theory: theory2, linear, 4 ᎠᎴ 8
  - theory: theory3, square, 3 ᎠᎴ 3
  - entry: theory1, 7 ᎠᎴ 54
  - theory: theory0, square, 4 ᎠᎴ 5
  - theory1 theory size 10
  - theory: theory1, ᎦᏍᎩᎶ, 0 ᎠᎴ 0
  - theory3 theory size 2
  - entry: theory1, 2 ᎠᎴ 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 ᎠᎴ 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ᎦᏍᎩᎶ form y = entry(x).
What smallest lossless theory?

Candidates:
  - entry: theory1, 0 5
  - entry: theory1, 5 30
  - theory: theory2, linear, 4 8
  - theory: theory3, square, 3 3
  - entry: theory1, 7 54
  - theory: theory0, square, 4 5
  - theory1 theory chhika 10
  - theory: theory1, patacha, 0 0
  - theory3 theory chhika 2
  - entry: theory1, 2 9
  - theory0 theory chhika 2
  - theory2 theory chhika 3
  - entry: theory1, 6 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Rules:
  - rule theory tiyay lossless iff it predict tukuy observation exactly
  - rule akllay lossless theory of least chhika
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; patacha form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory1, 0 ыкӏи 5
  - entry: theory1, 5 ыкӏи 30
  - тиориэ: theory2, linear, 4 ыкӏи 8
  - тиориэ: theory3, square, 3 ыкӏи 3
  - entry: theory1, 7 ыкӏи 54
  - тиориэ: theory0, square, 4 ыкӏи 5
  - theory1 10 тиориэ size
  - тиориэ: theory1, table, 0 ыкӏи 0
  - theory3 2 тиориэ size
  - entry: theory1, 2 ыкӏи 9
  - theory0 2 тиориэ size
  - theory2 3 тиориэ size
  - entry: theory1, 6 ыкӏи 41
Data:
  - 7 54 obs
  - 5 30 obs
  - 2 9 obs
  - 0 5 obs
  - 6 41 obs
Rules: rule тиориэ is lossless iff it predict every observation exactly; rule choose the lossless тиориэ of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless тиориэ сыд?

Candidates:
  - entry: theory1, 0 thiab 5
  - entry: theory1, 5 thiab 30
  - theory: theory2, linear, 4 thiab 8
  - theory: theory3, square, 3 thiab 3
  - entry: theory1, 7 thiab 54
  - theory: theory0, square, 4 thiab 5
  - theory1 theory size 10
  - theory: theory1, rooj, 0 thiab 0
  - theory3 theory size 2
  - entry: theory1, 2 thiab 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 thiab 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Cai: cai theory is lossless iff nws predict every observation exactly; cai choose lossless theory of least size.
Lub ntsiab: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; rooj form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory1, 0 5
  - entry: theory1, 5 30
  - theory: theory2, linear, 4 8
  - theory: theory3, square, 3 3
  - entry: theory1, 7 54
  - theory: theory0, square, 4 5
  - theory1 theory size 10
  - theory: theory1, table, 0 0
  - theory3 theory size 2
  - entry: theory1, 2 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of wy krook size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory ining-jak?

Candidates:
  - entry: theory1, 0 micha' 5
  - entry: theory1, 5 micha' 30
  - theory: theory2, linear, 4 micha' 8
  - theory: theory3, square, 3 micha' 3
  - entry: theory1, 7 micha' 54
  - theory: theory0, square, 4 micha' 5
  - theory1 theory size 10
  - theory: theory1, table, 0 micha' 0
  - theory3 theory size 2
  - entry: theory1, 2 micha' 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 micha' 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory nanta?

Candidates:
  - entry: theory1, 0 カ 5
  - entry: theory1, 5 カ 30
  - theory: theory2, linear, 4 カ 8
  - theory: theory3, square, 3 カ 3
  - entry: theory1, 7 カ 54
  - theory: theory0, square, 4 カ 5
  - theory1 10 theory size
  - theory: theory1, table, 0 カ 0
  - theory3 2 theory size
  - entry: theory1, 2 カ 9
  - theory0 2 theory size
  - theory2 3 theory size
  - entry: theory1, 6 カ 41
Data:
  - 7 54 obs
  - 5 30 obs
  - 2 9 obs
  - 0 5 obs
  - 6 41 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 ノカ; square y = x * x + p2 ノカ; constant y = p2 ノカ; table y = entry(x) ノカ.
Smallest lossless theory what?

Candidates:
  - entry: theory1, 0 ынкъам 5
  - entry: theory1, 5 ынкъам 30
  - theory: theory2, linear, 4 ынкъам 8
  - theory: theory3, square, 3 ынкъам 3
  - entry: theory1, 7 ынкъам 54
  - theory: theory0, square, 4 ынкъам 5
  - theory1 theory size 10
  - theory: theory1, table, 0 ынкъам 0
  - theory3 theory size 2
  - entry: theory1, 2 ынкъам 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 ынкъам 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory1, 0 yéetel 5
  - entry: theory1, 5 yéetel 30
  - theory: theory2, linear, 4 yéetel 8
  - theory: theory3, square, 3 yéetel 3
  - entry: theory1, 7 yéetel 54
  - theory: theory0, square, 4 yéetel 5
  - theory1 theory size 10
  - theory: theory1, table, 0 yéetel 0
  - theory3 theory size 2
  - entry: theory1, 2 yéetel 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 yéetel 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Rules:
  - rule theory yan lossless iff it predict every observation exactly
  - rule yéey lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory1, 0 5
  - entry: theory1, 5 30
  - theory: theory2, linear, 4 8
  - theory: theory3, square, 3 3
  - entry: theory1, 7 54
  - theory: theory0, square, 4 5
  - theory1 theory size 10
  - theory: theory1, mę́soną, 0 0
  - theory3 theory size 2
  - entry: theory1, 2 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Rules:
  - rule theory is lossless iff ą́wąną predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mę́soną form y = entry(x).
Smallest lossless theory híli?

Candidates:
  - entry: theory1, 0 na 5
  - entry: theory1, 5 na 30
  - theory: theory2, linear, 4 na 8
  - theory: theory3, square, 3 na 3
  - entry: theory1, 7 na 54
  - theory: theory0, square, 4 na 5
  - theory1 10 theory size
  - theory: theory1, table, 0 na 0
  - theory3 2 theory size
  - entry: theory1, 2 na 9
  - theory0 2 theory size
  - theory2 3 theory size
  - entry: theory1, 6 na 41
Data:
  - 7 54 obs
  - 5 30 obs
  - 2 9 obs
  - 0 5 obs
  - 6 41 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory1, 0 5
  - entry: theory1, 5 30
  - theory: theory2, linear, 4 8
  - theory: theory3, square, 3 3
  - entry: theory1, 7 54
  - theory: theory0, square, 4 5
  - theory1 theory size 10
  - theory: theory1, table, 0 0
  - theory3 theory size 2
  - entry: theory1, 2 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory1, 0 5
  - entry: theory1, 5 30
  - theory: theory2, linear, 4 8
  - theory: theory3, square, 3 3
  - entry: theory1, 7 54
  - theory: theory0, square, 4 5
  - theory1 10 theory size
  - theory: theory1, table, 0 0
  - theory3 2 theory size
  - entry: theory1, 2 9
  - theory0 2 theory size
  - theory2 3 theory size
  - entry: theory1, 6 41
Data:
  - 7 54 obs
  - 5 30 obs
  - 2 9 obs
  - 0 5 obs
  - 6 41 obs
Rules:
  - rule maya theory is lossless iff it predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory1, 0 ǂʻá 5
  - entry: theory1, 5 ǂʻá 30
  - theory: theory2, linear, 4 ǂʻá 8
  - theory: theory3, square, 3 ǂʻá 3
  - entry: theory1, 7 ǂʻá 54
  - theory: theory0, square, 4 ǂʻá 5
  - theory1 theory ʻǁnàhã 10
  - theory: theory1, table, 0 ǂʻá 0
  - theory3 theory ʻǁnàhã 2
  - entry: theory1, 2 ǂʻá 9
  - theory0 theory ʻǁnàhã 2
  - theory2 theory ʻǁnàhã 3
  - entry: theory1, 6 ǂʻá 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Rules:
  - rule theory ǀîi lossless iff èh predict every observation exactly
  - rule choose lossless theory of least ʻǁnàhã
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory1, 0 5
  - entry: theory1, 5 30
  - theory: theory2, linear, 4 8
  - theory: theory3, square, 3 3
  - entry: theory1, 7 54
  - theory: theory0, square, 4 5
  - theory1 10 theory size
  - theory: theory1, остол, 0 0
  - theory3 2 theory size
  - entry: theory1, 2 9
  - theory0 2 theory size
  - theory2 3 theory size
  - entry: theory1, 6 41
Data:
  - 7 54 obs
  - 5 30 obs
  - 2 9 obs
  - 0 5 obs
  - 6 41 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; остол y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory1, 0 5
  - entry: theory1, 5 30
  - theory: theory2, linear, 4 8
  - theory: theory3, square, 3 3
  - entry: theory1, 7 54
  - theory: theory0, square, 4 5
  - theory1 theory size 10
  - theory: theory1, table, 0 0
  - theory3 theory size 2
  - entry: theory1, 2 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory1, 0 5
  - entry: theory1, 5 30
  - theory: theory2, linear, 4 8
  - theory: theory3, square, 3 3
  - entry: theory1, 7 54
  - theory: theory0, square, 4 5
  - theory1 10 theory size
  - theory: theory1, table, 0 0
  - theory3 2 theory size
  - entry: theory1, 2 9
  - theory0 2 theory size
  - theory2 3 theory size
  - entry: theory1, 6 41
Data:
  - 7 54 obs
  - 5 30 obs
  - 2 9 obs
  - 0 5 obs
  - 6 41 obs
Rules:
  - rule theory is lossless iff kitu predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - entry: theory1, 0 5
  - entry: theory1, 5 30
  - theory: theory2, linear, 4 8
  - theory: theory3, square, 3 3
  - entry: theory1, 7 54
  - theory: theory0, square, 4 5
  - theory1 theory size 10
  - theory: theory1, mesa, 0 0
  - theory3 theory size 2
  - entry: theory1, 2 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mesa form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory1, 0 5
  - entry: theory1, 5 30
  - theory: theory2, linear, 4 8
  - theory: theory3, square, 3 3
  - entry: theory1, 7 54
  - theory: theory0, square, 4 5
  - theory1 theory size 10
  - theory: theory1, table, 0 0
  - theory3 theory size 2
  - entry: theory1, 2 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Rules:
  - rule theory nemi lossless iff yaja predict every observation exactly
  - rule choose ne lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ne table form y = entry(x).
Smallest lossless theory tay?

Les candidats sont:
  - article: theory1, 0 et 5
  - article: theory1, 5 et 30
  - théorie: theory2, linear, 4 et 8
  - théorie: theory3, square, 3 et 3
  - article: theory1, 7 et 54
  - théorie: theory0, square, 4 et 5
  - theory1 théorie taille 10
  - théorie: theory1, table, 0 et 0
  - theory3 théorie taille 2
  - article: theory1, 2 et 9
  - theory0 théorie taille 2
  - theory2 théorie taille 3
  - article: theory1, 6 et 41
Les données sont:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Les règles sont:
  - règle un théorie être lossless ssi il prédire tout observation exactement
  - règle choisir le lossless théorie du moindre taille
La sémantique est : linear former y = p1 * x + p2 ; square former y = x * x + p2 ; constant former y = p2 ; la table former y = entry(x).
Quoi smallest lossless théorie ?

Kandidato:
  - entry: theory1, 0 kaj 5
  - entry: theory1, 5 kaj 30
  - teorio: theory2, linear, 4 kaj 8
  - teorio: theory3, square, 3 kaj 3
  - entry: theory1, 7 kaj 54
  - teorio: theory0, square, 4 kaj 5
  - theory1 teorio grandeco 10
  - teorio: theory1, tablo, 0 kaj 0
  - theory3 teorio grandeco 2
  - entry: theory1, 2 kaj 9
  - theory0 teorio grandeco 2
  - theory2 teorio grandeco 3
  - entry: theory1, 6 kaj 41
Datumo:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Regulo: regulo teorio egali lossless iff ĝi predict ĉiu observo ekzakte; regulo elekti lossless teorio de plej malmulta grandeco.
Semantics: linear formi y = p1 * x + p2; square formi y = x * x + p2; constant formi y = p2; tablo formi y = entry(x).
Smallest lossless teorio kio?

Indulók:
  - szócikk: theory1, 0 és 5
  - szócikk: theory1, 5 és 30
  - elmélet: theory2, linear, 4 és 8
  - elmélet: theory3, square, 3 és 3
  - szócikk: theory1, 7 és 54
  - elmélet: theory0, square, 4 és 5
  - theory1 elmélet méret 10
  - elmélet: theory1, asztal, 0 és 0
  - theory3 elmélet méret 2
  - szócikk: theory1, 2 és 9
  - theory0 elmélet méret 2
  - theory2 elmélet méret 3
  - szócikk: theory1, 6 és 41
Adat:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Szabályok:
  - szabály elmélet van veszteségmentes acsa az megjósol minden megfigyelés pontosan
  - szabály kiválaszt a veszteségmentes elmélet of legkisebb méret
Szemantika: linear kialakít y = p1 * x + p2; square kialakít y = x * x + p2; constant kialakít y = p2; a asztal kialakít y = entry(x).
Smallest veszteségmentes elmélet melyik?

候選人:
  - entry:theory1, 0及5
  - entry:theory1, 5及30
  - theory:theory2, linear, 4及8
  - theory:theory3, square, 3及3
  - entry:theory1, 7及54
  - theory:theory0, square, 4及5
  - theory1theory size10
  - theory:theory1, 檯, 0及0
  - theory3theory size2
  - entry:theory1, 2及9
  - theory0theory size2
  - theory2theory size3
  - entry:theory1, 6及41
數據:
  - 7obs54
  - 5obs30
  - 2obs9
  - 0obs5
  - 6obs41
rules:rule:一theory是losslessiffitpredict每observationexactly; rule:揀losslesstheory...嘅leastsize.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; 檯formy = entry(x).
smallest lossless theory乜嘢?

Candidates:
  - entry: theory1, 0 とぅ 5
  - entry: theory1, 5 とぅ 30
  - theory: theory2, linear, 4 とぅ 8
  - theory: theory3, square, 3 とぅ 3
  - entry: theory1, 7 とぅ 54
  - theory: theory0, square, 4 とぅ 5
  - theory1 theory size 10
  - theory: theory1, table, 0 とぅ 0
  - theory3 theory size 2
  - entry: theory1, 2 とぅ 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 とぅ 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Rules: rule theory 有ん lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Үміткер:
  - entry: theory1, 0 және 5
  - entry: theory1, 5 және 30
  - теория: theory2, linear, 4 және 8
  - теория: theory3, square, 3 және 3
  - entry: theory1, 7 және 54
  - теория: theory0, square, 4 және 5
  - theory1 теория мөлшер 10
  - теория: theory1, үстел, 0 және 0
  - theory3 теория мөлшер 2
  - entry: theory1, 2 және 9
  - theory0 теория мөлшер 2
  - theory2 теория мөлшер 3
  - entry: theory1, 6 және 41
Деректер:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Ереже: ереже теория is lossless iff ол predict әр бақылау exactly; ереже таңдау lossless теория туралы least мөлшер.
Семантикалық: linear пішін y = p1 * x + p2; square пішін y = x * x + p2; constant пішін y = p2; үстел пішін y = entry(x).
Smallest lossless теория не?

מועמדת:
  - entry: theory1, 0 וְ־ 5
  - entry: theory1, 5 וְ־ 30
  - תּוֹרָה: theory2, linear, 4 וְ־ 8
  - תּוֹרָה: theory3, square, 3 וְ־ 3
  - entry: theory1, 7 וְ־ 54
  - תּוֹרָה: theory0, square, 4 וְ־ 5
  - theory1 תּוֹרָה גֹּדֶל 10
  - תּוֹרָה: theory1, טַבְלָה, 0 וְ־ 0
  - theory3 תּוֹרָה גֹּדֶל 2
  - entry: theory1, 2 וְ־ 9
  - theory0 תּוֹרָה גֹּדֶל 2
  - theory2 תּוֹרָה גֹּדֶל 3
  - entry: theory1, 6 וְ־ 41
נְתוּנִים:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
מָשַׁל:
  - מָשַׁל אַחַת תּוֹרָה הוא lossless אםם זֶה predict כֹּל תַּצְפִּית בדיוק
  - מָשַׁל בחר ה־ lossless תּוֹרָה שֶׁל least גֹּדֶל
תורת המשמעים: linear צורה y = p1 * x + p2; square צורה y = x * x + p2; constant צורה y = p2; טַבְלָה ה־ צורה y = entry(x).
איזה smallest lossless תּוֹרָה?

Candidates:
  - entry: theory1, 0 დო 5
  - entry: theory1, 5 დო 30
  - theory: theory2, linear, 4 დო 8
  - theory: theory3, square, 3 დო 3
  - entry: theory1, 7 დო 54
  - theory: theory0, square, 4 დო 5
  - theory1 theory size 10
  - theory: theory1, table, 0 დო 0
  - theory3 theory size 2
  - entry: theory1, 2 დო 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 დო 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Kandidat:
  - lema: theory1, 0 dan 5
  - lema: theory1, 5 dan 30
  - teori: theory2, linear, 4 dan 8
  - teori: theory3, square, 3 dan 3
  - lema: theory1, 7 dan 54
  - teori: theory0, square, 4 dan 5
  - theory1 teori ukuran 10
  - teori: theory1, meja, 0 dan 0
  - theory3 teori ukuran 2
  - lema: theory1, 2 dan 9
  - theory0 teori ukuran 2
  - theory2 teori ukuran 3
  - lema: theory1, 6 dan 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Rules:
  - rule teori berada lossless iff it predict setiap observation tepat
  - rule memilih si lossless teori dari least ukuran
Semantik: linear formulir y = p1 * x + p2; square formulir y = x * x + p2; constant formulir y = p2; meja si formulir y = entry(x).
Smallest lossless teori apa?

បេក្ខជន:
  - មេពាក្យ:theory1, 0នឹង5
  - មេពាក្យ:theory1, 5នឹង30
  - ទ្រឹស្ដី:theory2, linear, 4នឹង8
  - ទ្រឹស្ដី:theory3, square, 3នឹង3
  - មេពាក្យ:theory1, 7នឹង54
  - ទ្រឹស្ដី:theory0, square, 4នឹង5
  - theory1ទ្រឹស្ដីទំហំ10
  - ទ្រឹស្ដី:theory1, តុ, 0នឹង0
  - theory3ទ្រឹស្ដីទំហំ2
  - មេពាក្យ:theory1, 2នឹង9
  - theory0ទ្រឹស្ដីទំហំ2
  - theory2ទ្រឹស្ដីទំហំ3
  - មេពាក្យ:theory1, 6នឹង41
ទិន្នន័យ:
  - 7obs54
  - 5obs30
  - 2obs9
  - 0obs5
  - 6obs41
ក្បួន:ក្បួន:ទ្រឹស្ដីត្រូវបានlosslessiffវាចាប់យាមរាល់គំនន់exactly; ក្បួន:រើសthelosslessទ្រឹស្ដីនៃleastទំហំ.
និឃណ្ដសាស្ត្រ:linearគ្រោងy = p1 * x + p2; squareគ្រោងy = x * x + p2; constantគ្រោងy = p2; តុគ្រោងy = entry(x).
smallestlosslessទ្រឹស្ដីអី?

ຜູ້ສະໝັກ:
  - entry:theory1, 0ແລະ5
  - entry:theory1, 5ແລະ30
  - ທິດສະດີ:theory2, linear, 4ແລະ8
  - ທິດສະດີ:theory3, square, 3ແລະ3
  - entry:theory1, 7ແລະ54
  - ທິດສະດີ:theory0, square, 4ແລະ5
  - theory1ທິດສະດີຂະຫນາດ10
  - ທິດສະດີ:theory1, ໂຕະ, 0ແລະ0
  - theory3ທິດສະດີຂະຫນາດ2
  - entry:theory1, 2ແລະ9
  - theory0ທິດສະດີຂະຫນາດ2
  - theory2ທິດສະດີຂະຫນາດ3
  - entry:theory1, 6ແລະ41
ຂໍ້ມູນ:
  - 7obs54
  - 5obs30
  - 2obs9
  - 0obs5
  - 6obs41
ກະຕິກາ:ກະຕິກາ:ທິດສະດີຢູ່losslessiffມັນທຳນວາຍທຸກobservationexactly; ກະຕິກາ:ເລືອກlosslessທິດສະດີຂອງleastຂະຫນາດ.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; ໂຕະformy = entry(x).
smallestlosslessທິດສະດີຫຍັງ?

candidates:
  - entry: theory1, 0 మరియు 5
  - entry: theory1, 5 మరియు 30
  - theory: theory2, linear, 4 మరియు 8
  - theory: theory3, square, 3 మరియు 3
  - entry: theory1, 7 మరియు 54
  - theory: theory0, square, 4 మరియు 5
  - theory1 10 theory size
  - theory: theory1, బల్ల, 0 మరియు 0
  - theory3 2 theory size
  - entry: theory1, 2 మరియు 9
  - theory0 2 theory size
  - theory2 3 theory size
  - entry: theory1, 6 మరియు 41
data:
  - 7 54 obs
  - 5 30 obs
  - 2 9 obs
  - 0 5 obs
  - 6 41 obs
నియమం: నియమం theory ఉండు lossless iff it predict ప్రతి పరిశీలన exactly; నియమం choose lossless theory of least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; బల్ల y = entry(x) form.
smallest lossless theory ఏమిటి?

Candidates:
  - entry: theory1, 0 5
  - entry: theory1, 5 30
  - theory: theory2, linear, 4 8
  - theory: theory3, square, 3 3
  - entry: theory1, 7 54
  - theory: theory0, square, 4 5
  - theory1 theory size 10
  - theory: theory1, table, 0 0
  - theory3 theory size 2
  - entry: theory1, 2 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Rules: rule theory wà lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
What smallest lossless theory?

Candidates:
  - entry: theory1, 0 5
  - entry: theory1, 5 30
  - theory: theory2, linear, 4 8
  - theory: theory3, square, 3 3
  - entry: theory1, 7 54
  - theory: theory0, square, 4 5
  - theory1 10 theory size
  - theory: theory1, table, 0 0
  - theory3 2 theory size
  - entry: theory1, 2 9
  - theory0 2 theory size
  - theory2 3 theory size
  - entry: theory1, 6 41
Data:
  - 7 54 obs
  - 5 30 obs
  - 2 9 obs
  - 0 5 obs
  - 6 41 obs
Rules:
  - rule theory naiágúóli lossless iff it predict every observation exactly
  - rule choose the lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

candidates:
  - entry: theory1, 0 5
  - entry: theory1, 5 30
  - theory: theory2, linear, 4 8
  - theory: theory3, square, 3 3
  - entry: theory1, 7 54
  - theory: theory0, square, 4 5
  - theory1 theory size 10
  - theory: theory1, table, 0 0
  - theory3 theory size 2
  - entry: theory1, 2 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 41
data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
smallest lossless theory what?

Candidates:
  - entry: theory1, 0 5
  - entry: theory1, 5 30
  - theory: theory2, linear, 4 8
  - theory: theory3, square, 3 3
  - entry: theory1, 7 54
  - theory: theory0, square, 4 5
  - theory1 theory size 10
  - theory: theory1, tafra, 0 0
  - theory3 theory size 2
  - entry: theory1, 2 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; tafra form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory1, 0 5
  - entry: theory1, 5 30
  - theory: theory2, linear, 4 8
  - theory: theory3, square, 3 3
  - entry: theory1, 7 54
  - theory: theory0, square, 4 5
  - theory1 theory size 10
  - theory: theory1, táxemésėhestȯtse, 0 0
  - theory3 theory size 2
  - entry: theory1, 2 9
  - theory0 theory size 2
  - theory2 theory size 3
  - entry: theory1, 6 41
Data:
  - 7 obs 54
  - 5 obs 30
  - 2 obs 9
  - 0 obs 5
  - 6 obs 41
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; táxemésėhestȯtse form y = entry(x).
Smallest lossless theory what?

Candidates:
  - entry: theory1, 0 5
  - entry: theory1, 5 30
  - theory: theory2, linear, 4 8
  - theory: theory3, square, 3 3
  - entry: theory1, 7 54
  - theory: theory0, square, 4 5
  - theory1 10 theory size
  - theory: theory1, ствал, 0 0
  - theory3 2 theory size
  - entry: theory1, 2 9
  - theory0 2 theory size
  - theory2 3 theory size
  - entry: theory1, 6 41
Data:
  - 7 54 obs
  - 5 30 obs
  - 2 9 obs
  - 0 5 obs
  - 6 41 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; ствал y = entry(x) form.
Smallest lossless theory вуч?

The candidates are:
  - theory: theory0, square, 4 and -1
  - entry: theory1, 3 and 8
  - theory3 theory size 3
  - entry: theory1, 10 and 99
  - theory2 theory size 2
  - entry: theory1, 2 and 3
  - entry: theory1, 12 and 143
  - theory: theory1, table, 0 and 0
  - theory1 theory size 10
  - entry: theory1, 11 and 120
  - theory0 theory size 2
  - theory: theory3, linear, 7 and -1
  - theory: theory2, square, 3 and -3
The data are:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

Los candidatos son:
  - la teoría: theory0, square, 4 y -1
  - la entrada: theory1, 3 y 8
  - theory3 el tamaño de la teoría 3
  - la entrada: theory1, 10 y 99
  - theory2 el tamaño de la teoría 2
  - la entrada: theory1, 2 y 3
  - la entrada: theory1, 12 y 143
  - la teoría: theory1, mesa, 0 y 0
  - theory1 el tamaño de la teoría 10
  - la entrada: theory1, 11 y 120
  - theory0 el tamaño de la teoría 2
  - la teoría: theory3, linear, 7 y -1
  - la teoría: theory2, square, 3 y -3
Los datos son:
  - 3 la observación 8
  - 12 la observación 143
  - 11 la observación 120
  - 2 la observación 3
  - 10 la observación 99
Las reglas son:
  - la regla: a la teoría es lossless si y sólo si it predice every observation exactamente
  - la regla: choose el lossless la teoría de least tamaño
La semántica es: linear la forma y = p1 * x + p2; square la forma y = x * x + p2; constant la forma y = p2; la mesa la forma y = entry(x).
¿Qué smallest lossless la teoría?

候选项如下：
  - 的理论是：theory0、square、4和-1
  - 的条目是：theory1、3和8
  - theory3的理论规模是3
  - 的条目是：theory1、10和99
  - theory2的理论规模是2
  - 的条目是：theory1、2和3
  - 的条目是：theory1、12和143
  - 的理论是：theory1、桌子、0和0
  - theory1的理论规模是10
  - 的条目是：theory1、11和120
  - theory0的理论规模是2
  - 的理论是：theory3、linear、7和-1
  - 的理论是：theory2、square、3和-3
数据如下：
  - 3观察到8
  - 12观察到143
  - 11观察到120
  - 2观察到3
  - 10观察到99
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

Adaylar:
  - kuram: theory0, square, 4 ve -1
  - entry: theory1, 3 ve 8
  - theory3 3 kuram boyut
  - entry: theory1, 10 ve 99
  - theory2 2 kuram boyut
  - entry: theory1, 2 ve 3
  - entry: theory1, 12 ve 143
  - kuram: theory1, masa, 0 ve 0
  - theory1 10 kuram boyut
  - entry: theory1, 11 ve 120
  - theory0 2 kuram boyut
  - kuram: theory3, linear, 7 ve -1
  - kuram: theory2, square, 3 ve -3
Veriler:
  - 3 8 obs
  - 12 143 obs
  - 11 120 obs
  - 2 3 obs
  - 10 99 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

Wagombea ni:
  - theory: theory0, square, 4 na -1
  - entry: theory1, 3 na 8
  - theory3 theory size 3
  - entry: theory1, 10 na 99
  - theory2 theory size 2
  - entry: theory1, 2 na 3
  - entry: theory1, 12 na 143
  - theory: theory1, meza, 0 na 0
  - theory1 theory size 10
  - entry: theory1, 11 na 120
  - theory0 theory size 2
  - theory: theory3, linear, 7 na -1
  - theory: theory2, square, 3 na -3
Data:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

The candidates are:
  - theory: theory0, square, 4 and -1
  - entry: theory1, 3 and 8
  - theory3 theory size 3
  - entry: theory1, 10 and 99
  - theory2 theory size 2
  - entry: theory1, 2 and 3
  - entry: theory1, 12 and 143
  - theory: theory1, table, 0 and 0
  - theory1 theory size 10
  - entry: theory1, 11 and 120
  - theory0 theory size 2
  - theory: theory3, linear, 7 and -1
  - theory: theory2, square, 3 and -3
The data are:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
The rules are:
  - rule a theory is lossless if and only if it predicts every observation exactly
  - rule choose the lossless theory of least size
The semantics are: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; the table form y = entry(x).
What is the smallest lossless theory?

{candidates: [(theory theory0 square 4 -1) (entry theory1 3 8) (theory_size theory3 3) (entry theory1 10 99) (theory_size theory2 2) (entry theory1 2 3) (entry theory1 12 143) (theory theory1 table 0 0) (theory_size theory1 10) (entry theory1 11 120) (theory_size theory0 2) (theory theory3 linear 7 -1) (theory theory2 square 3 -3)], data: [(obs 3 8) (obs 12 143) (obs 11 120) (obs 2 3) (obs 10 99)], query: smallest_lossless_theory, rules: [(rule (a_theory_is_lossless_iff_it_predicts_every_observation_exactly)) (rule (choose_the_lossless_theory_of_least_size))], semantics: [(form linear "y = p1 * x + p2") (form square "y = x * x + p2") (form constant "y = p2") (form table "y = entry(x)")]}

Die Kandidaten sind:
  - Theorie: theory0, square, 4 und -1
  - Eintrag: theory1, 3 und 8
  - theory3 Theorie Größe 3
  - Eintrag: theory1, 10 und 99
  - theory2 Theorie Größe 2
  - Eintrag: theory1, 2 und 3
  - Eintrag: theory1, 12 und 143
  - Theorie: theory1, Tisch, 0 und 0
  - theory1 Theorie Größe 10
  - Eintrag: theory1, 11 und 120
  - theory0 Theorie Größe 2
  - Theorie: theory3, linear, 7 und -1
  - Theorie: theory2, square, 3 und -3
Die Daten sind:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Die Regeln sind:
  - Regel ein Theorie werden verlustfrei gdw. er vorhersagen jeder Beobachtung genau
  - Regel wählen der verlustfrei Theorie aus geringst Größe
Die Semantik ist: linear formen y = p1 * x + p2; square formen y = x * x + p2; constant formen y = p2; der Tisch formen y = entry(x).
Was smallest verlustfrei Theorie?

Кандѝда̄т:
  - тѐо̄рија: theory0, square, 4 и -1
  - одредница: theory1, 3 и 8
  - theory3 тѐо̄рија величѝна 3
  - одредница: theory1, 10 и 99
  - theory2 тѐо̄рија величѝна 2
  - одредница: theory1, 2 и 3
  - одредница: theory1, 12 и 143
  - тѐо̄рија: theory1, сто̑л, 0 и 0
  - theory1 тѐо̄рија величѝна 10
  - одредница: theory1, 11 и 120
  - theory0 тѐо̄рија величѝна 2
  - тѐо̄рија: theory3, linear, 7 и -1
  - тѐо̄рија: theory2, square, 3 и -3
Податци:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Пра̏вило:
  - пра̏вило тѐо̄рија би̏ти lossless iff оно predvidjeti сва̏кӣ опа́жа̄ње тачно
  - пра̏вило изабрати lossless тѐо̄рија od minimalan величѝна
Сема̀нтика: linear oblik y = p1 * x + p2; square oblik y = x * x + p2; constant oblik y = p2; сто̑л oblik y = entry(x).
Smallest lossless тѐо̄рија kakav?

Ehdokkaat:
  - teoria: theory0, square, 4 ja -1
  - artikkeli: theory1, 3 ja 8
  - theory3 teoria koko 3
  - artikkeli: theory1, 10 ja 99
  - theory2 teoria koko 2
  - artikkeli: theory1, 2 ja 3
  - artikkeli: theory1, 12 ja 143
  - teoria: theory1, pöytä, 0 ja 0
  - theory1 teoria koko 10
  - artikkeli: theory1, 11 ja 120
  - theory0 teoria koko 2
  - teoria: theory3, linear, 7 ja -1
  - teoria: theory2, square, 3 ja -3
Tieto:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Säännöt:
  - sääntö teoria tulla häviötön joss se ennakoida jokainen havainnointi täsmälleen
  - sääntö valita häviötön teoria vaille vähin koko
Semantiikka: linear muotoilla y = p1 * x + p2; square muotoilla y = x * x + p2; constant muotoilla y = p2; pöytä muotoilla y = entry(x).
Mikä smallest häviötön teoria?

候选项如下：
  - 的理论是：theory0、square、4和-1
  - 的条目是：theory1、3和8
  - theory3的理论规模是3
  - 的条目是：theory1、10和99
  - theory2的理论规模是2
  - 的条目是：theory1、2和3
  - 的条目是：theory1、12和143
  - 的理论是：theory1、桌子、0和0
  - theory1的理论规模是10
  - 的条目是：theory1、11和120
  - theory0的理论规模是2
  - 的理论是：theory3、linear、7和-1
  - 的理论是：theory2、square、3和-3
数据如下：
  - 3观察到8
  - 12观察到143
  - 11观察到120
  - 2观察到3
  - 10观察到99
规则如下：规则：一的理论是是lossless当且仅当it预测everyobservation恰好是；规则：choose这lossless的理论是的least大小。
语义如下：linear的形式是y = p1 * x + p2；square的形式是y = x * x + p2；constant的形式是y = p2；这张桌子的形式是y = entry(x)。
smallestlossless的理论是什么？

候補者:
  - 理論:theory0, square, 4と-1
  - 項目:theory1, 3と8
  - theory33理論大きさ
  - 項目:theory1, 10と99
  - theory22理論大きさ
  - 項目:theory1, 2と3
  - 項目:theory1, 12と143
  - 理論:theory1, 台, 0と0
  - theory110理論大きさ
  - 項目:theory1, 11と120
  - theory02理論大きさ
  - 理論:theory3, linear, 7と-1
  - 理論:theory2, square, 3と-3
資料:
  - 38obs
  - 12143obs
  - 11120obs
  - 23obs
  - 1099obs
規則:規則:理論れるロスレスiffこれ予言する凡ゆる観察正確に; 規則:選ぶロスレス理論の中の最小の大きさ.
意味論:lineary = p1 * x + p2形作る; squarey = x * x + p2形作る; constanty = p2形作る; 台y = entry(x)形作る.
smallestロスレス理論何と?

Adaylar:
  - kuram: theory0, square, 4 ve -1
  - entry: theory1, 3 ve 8
  - theory3 3 kuram boyut
  - entry: theory1, 10 ve 99
  - theory2 2 kuram boyut
  - entry: theory1, 2 ve 3
  - entry: theory1, 12 ve 143
  - kuram: theory1, masa, 0 ve 0
  - theory1 10 kuram boyut
  - entry: theory1, 11 ve 120
  - theory0 2 kuram boyut
  - kuram: theory3, linear, 7 ve -1
  - kuram: theory2, square, 3 ve -3
Veriler:
  - 3 8 obs
  - 12 143 obs
  - 11 120 obs
  - 2 3 obs
  - 10 99 obs
Kurallar:
  - kural: bir kuram lossless iff it öngörür every observation exactly
  - kural: choose lossless kuram least boyut
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; masa y = entry(x) form.
Smallest lossless kuram ne?

مُرَشَّح:
  - نَظَرِيَّة: theory0، square، 4 وَـ -1
  - مَدْخَل: theory1، 3 وَـ 8
  - نَظَرِيَّة مَقَاس theory3 3
  - مَدْخَل: theory1، 10 وَـ 99
  - نَظَرِيَّة مَقَاس theory2 2
  - مَدْخَل: theory1، 2 وَـ 3
  - مَدْخَل: theory1، 12 وَـ 143
  - نَظَرِيَّة: theory1، طَاوِلَة، 0 وَـ 0
  - نَظَرِيَّة مَقَاس theory1 10
  - مَدْخَل: theory1، 11 وَـ 120
  - نَظَرِيَّة مَقَاس theory0 2
  - نَظَرِيَّة: theory3، linear، 7 وَـ -1
  - نَظَرِيَّة: theory2، square، 3 وَـ -3
بَيَانَات:
  - obs 3 8
  - obs 12 143
  - obs 11 120
  - obs 2 3
  - obs 10 99
قَانُون:
  - قَانُون نَظَرِيَّة كَانَ lossless iff هُوَ تَنَبَّأَ كُلّ رَصْد بِالضَّبْط
  - قَانُون اِخْتَارَ الـ lossless نَظَرِيَّة مِنْ أَقَلَّ مَقَاس
عِلْم اَلْمَعَانِي: شَكَّلَ linear y = p1 * x + p2؛ شَكَّلَ square y = x * x + p2؛ شَكَّلَ constant y = p2؛ شَكَّلَ الـ طَاوِلَة y = entry(x).
smallest lossless نَظَرِيَّة مَاذَا؟

Კანდიდატები:
  - თეორია: theory0, square, 4 და -1
  - სასათაურო სიტყვა: theory1, 3 და 8
  - theory3 3 თეორია ზომა
  - სასათაურო სიტყვა: theory1, 10 და 99
  - theory2 2 თეორია ზომა
  - სასათაურო სიტყვა: theory1, 2 და 3
  - სასათაურო სიტყვა: theory1, 12 და 143
  - თეორია: theory1, მაგიდა, 0 და 0
  - theory1 10 თეორია ზომა
  - სასათაურო სიტყვა: theory1, 11 და 120
  - theory0 2 თეორია ზომა
  - თეორია: theory3, linear, 7 და -1
  - თეორია: theory2, square, 3 და -3
Მონაცემები:
  - 3 8 obs
  - 12 143 obs
  - 11 120 obs
  - 2 3 obs
  - 10 99 obs
Წესი:
  - წესი თეორია ყოფნა უდანაკარგო iff ის predict ყველა დაკვირვება ზუსტად
  - წესი ამორჩევა უდანაკარგო თეორია of least ზომა
Სემანტიკა: linear y = p1 * x + p2 ბლანკი; square y = x * x + p2 ბლანკი; constant y = p2 ბლანკი; მაგიდა y = entry(x) ბლანკი.
Smallest უდანაკარგო თეორია რა?

Kaiwhakauru:
  - ariā: theory0, square, 4 me -1
  - tāurunga: theory1, 3 me 8
  - ariā size theory3 3
  - tāurunga: theory1, 10 me 99
  - ariā size theory2 2
  - tāurunga: theory1, 2 me 3
  - tāurunga: theory1, 12 me 143
  - ariā: theory1, tēpu, 0 me 0
  - ariā size theory1 10
  - tāurunga: theory1, 11 me 120
  - ariā size theory0 2
  - ariā: theory3, linear, 7 me -1
  - ariā: theory2, square, 3 me -3
Hōtuku:
  - obs 3 8
  - obs 12 143
  - obs 11 120
  - obs 2 3
  - obs 10 99
Rekureihana:
  - rekureihana ariā is lossless iff it matakite every observation pū
  - rekureihana whiri te lossless ariā o least size
Semantics: āhua linear y = p1 * x + p2; āhua square y = x * x + p2; āhua constant y = p2; āhua te tēpu y = entry(x).
Smallest lossless ariā unutai?

Candidates:
  - lý thuyết: theory0, square, 4 và -1
  - mục từ: theory1, 3 và 8
  - theory3 lý thuyết kích thước 3
  - mục từ: theory1, 10 và 99
  - theory2 lý thuyết kích thước 2
  - mục từ: theory1, 2 và 3
  - mục từ: theory1, 12 và 143
  - lý thuyết: theory1, bàn, 0 và 0
  - theory1 lý thuyết kích thước 10
  - mục từ: theory1, 11 và 120
  - theory0 lý thuyết kích thước 2
  - lý thuyết: theory3, linear, 7 và -1
  - lý thuyết: theory2, square, 3 và -3
Dữ liệu:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Quy tắc:
  - quy tắc lý thuyết được lossless iff nó dự báo mỗi observation đúng rồi
  - quy tắc chọn the lossless lý thuyết bằng least kích thước
Ngữ nghĩa: linear làm thành y = p1 * x + p2; square làm thành y = x * x + p2; constant làm thành y = p2; bàn làm thành y = entry(x).
Smallest lossless lý thuyết gì?

ผู้สมัคร:
  - ทฤษฎี:theory0, square, 4และ-1
  - entry:theory1, 3และ8
  - theory3ทฤษฎีขนาด3
  - entry:theory1, 10และ99
  - theory2ทฤษฎีขนาด2
  - entry:theory1, 2และ3
  - entry:theory1, 12และ143
  - ทฤษฎี:theory1, โต๊ะ, 0และ0
  - theory1ทฤษฎีขนาด10
  - entry:theory1, 11และ120
  - theory0ทฤษฎีขนาด2
  - ทฤษฎี:theory3, linear, 7และ-1
  - ทฤษฎี:theory2, square, 3และ-3
ข้อมูล:
  - 3obs8
  - 12obs143
  - 11obs120
  - 2obs3
  - 10obs99
กฎ:กฎ:ทฤษฎีถูกlosslessiffมันทำนายทุกการสังเกตexactly; กฎ:เลือกlosslessทฤษฎีของleastขนาด.
อรรถศาสตร์:linearรูปร่างy = p1 * x + p2; squareรูปร่างy = x * x + p2; constantรูปร่างy = p2; โต๊ะรูปร่างy = entry(x).
smallestlosslessทฤษฎีอะไร?

வேட்பாளர்:
  - theory: theory0, square, 4 மற்றும் -1
  - உள்நுழைவதற்கு அனுமதி: theory1, 3 மற்றும் 8
  - theory3 3 theory size
  - உள்நுழைவதற்கு அனுமதி: theory1, 10 மற்றும் 99
  - theory2 2 theory size
  - உள்நுழைவதற்கு அனுமதி: theory1, 2 மற்றும் 3
  - உள்நுழைவதற்கு அனுமதி: theory1, 12 மற்றும் 143
  - theory: theory1, மேசை, 0 மற்றும் 0
  - theory1 10 theory size
  - உள்நுழைவதற்கு அனுமதி: theory1, 11 மற்றும் 120
  - theory0 2 theory size
  - theory: theory3, linear, 7 மற்றும் -1
  - theory: theory2, square, 3 மற்றும் -3
தரவுகள்:
  - 3 8 obs
  - 12 143 obs
  - 11 120 obs
  - 2 3 obs
  - 10 99 obs
rules: rule theory படு lossless iff it கணி ஒவ்வொரு observation exactly; rule choose lossless theory கொண்ட least size.
semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; மேசை y = entry(x) form.
smallest lossless theory என்ன?

Wagombea ni:
  - theory: theory0, square, 4 na -1
  - entry: theory1, 3 na 8
  - theory3 theory size 3
  - entry: theory1, 10 na 99
  - theory2 theory size 2
  - entry: theory1, 2 na 3
  - entry: theory1, 12 na 143
  - theory: theory1, meza, 0 na 0
  - theory1 theory size 10
  - entry: theory1, 11 na 120
  - theory0 theory size 2
  - theory: theory3, linear, 7 na -1
  - theory: theory2, square, 3 na -3
Data:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Sheria ni:
  - sheria: theory ni lossless iff it predict every observation exactly
  - sheria: choose lossless theory ya least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; meza form y = entry(x).
Smallest lossless theory nini?

Candidates:
  - theory: theory0, square, 4 dóó -1
  - entry: theory1, 3 dóó 8
  - theory3 3 theory size
  - entry: theory1, 10 dóó 99
  - theory2 2 theory size
  - entry: theory1, 2 dóó 3
  - entry: theory1, 12 dóó 143
  - theory: theory1, bikááʼ adání, 0 dóó 0
  - theory1 10 theory size
  - entry: theory1, 11 dóó 120
  - theory0 2 theory size
  - theory: theory3, linear, 7 dóó -1
  - theory: theory2, square, 3 dóó -3
Data:
  - 3 8 obs
  - 12 143 obs
  - 11 120 obs
  - 2 3 obs
  - 10 99 obs
Bee hazʼáanii:
  - bee hazʼáanii theory átʼé lossless iff it predict every observation exactly
  - bee hazʼáanii choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; bikááʼ adání y = entry(x) form.
Smallest lossless theory haʼátʼíísh?

Candidates:
  - theory: theory0, square, 4 aamma -1
  - entry: theory1, 3 aamma 8
  - theory3 3 theory size
  - entry: theory1, 10 aamma 99
  - theory2 2 theory size
  - entry: theory1, 2 aamma 3
  - entry: theory1, 12 aamma 143
  - theory: theory1, table, 0 aamma 0
  - theory1 10 theory size
  - entry: theory1, 11 aamma 120
  - theory0 2 theory size
  - theory: theory3, linear, 7 aamma -1
  - theory: theory2, square, 3 aamma -3
Data:
  - 3 8 obs
  - 12 143 obs
  - 11 120 obs
  - 2 3 obs
  - 10 99 obs
Rules: rule theory a lossless iff una predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 blanketti; square y = x * x + p2 blanketti; constant y = p2 blanketti; table y = entry(x) blanketti.
Smallest lossless theory what?

Candidates:
  - theory: theory0, square, 4 na -1
  - entry: theory1, 3 na 8
  - theory3 theory size 3
  - entry: theory1, 10 na 99
  - theory2 theory size 2
  - entry: theory1, 2 na 3
  - entry: theory1, 12 na 143
  - theory: theory1, table, 0 na 0
  - theory1 theory size 10
  - entry: theory1, 11 na 120
  - theory0 theory size 2
  - theory: theory3, linear, 7 na -1
  - theory: theory2, square, 3 na -3
Data:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory bilong least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory0, square, 4 -1
  - entry: theory1, 3 8
  - theory3 theory size 3
  - entry: theory1, 10 99
  - theory2 theory size 2
  - entry: theory1, 2 3
  - entry: theory1, 12 143
  - theory: theory1, table, 0 0
  - theory1 theory size 10
  - entry: theory1, 11 120
  - theory0 theory size 2
  - theory: theory3, linear, 7 -1
  - theory: theory2, square, 3 -3
Data:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Nikanixi:
  - nikanixi theory is lossless iff it predict every observation exactly
  - nikanixi choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory kwèch?

Candidates:
  - theory: theory0, square, 4 а -1
  - entry: theory1, 3 а 8
  - theory3 theory size 3
  - entry: theory1, 10 а 99
  - theory2 theory size 2
  - entry: theory1, 2 а 3
  - entry: theory1, 12 а 143
  - theory: theory1, table, 0 а 0
  - theory1 theory size 10
  - entry: theory1, 11 а 120
  - theory0 theory size 2
  - theory: theory3, linear, 7 а -1
  - theory: theory2, square, 3 а -3
Data:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Rules:
  - rule theory хила lossless iff it predict дерриг observation exactly
  - rule хержа lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory фу?

후보자:
  - 이론: theory0, square, 4 -1
  - 항목: theory1, 3 8
  - theory3 3 이론 크기
  - 항목: theory1, 10 99
  - theory2 2 이론 크기
  - 항목: theory1, 2 3
  - 항목: theory1, 12 143
  - 이론: theory1, 테이블, 0 0
  - theory1 10 이론 크기
  - 항목: theory1, 11 120
  - theory0 2 이론 크기
  - 이론: theory3, linear, 7 -1
  - 이론: theory2, square, 3 -3
자료:
  - 3 8 obs
  - 12 143 obs
  - 11 120 obs
  - 2 3 obs
  - 10 99 obs
규칙: 규칙 이론 is lossless iff 이것 예언하다 각 관찰 정확하게; 규칙 고르다 lossless 이론...의 가장 적게 크기.
의미론: linear y = p1 * x + p2 형상; square y = x * x + p2 형상; constant y = p2 형상; 테이블 y = entry(x) 형상.
smallest lossless 이론 무엇?

Kandidatu:
  - theory: theory0, square, 4 eta -1
  - sarrera: theory1, 3 eta 8
  - theory3 3 theory tamaina
  - sarrera: theory1, 10 eta 99
  - theory2 2 theory tamaina
  - sarrera: theory1, 2 eta 3
  - sarrera: theory1, 12 eta 143
  - theory: theory1, mahai, 0 eta 0
  - theory1 10 theory tamaina
  - sarrera: theory1, 11 eta 120
  - theory0 2 theory tamaina
  - theory: theory3, linear, 7 eta -1
  - theory: theory2, square, 3 eta -3
Data:
  - 3 8 obs
  - 12 143 obs
  - 11 120 obs
  - 2 3 obs
  - 10 99 obs
Arau:
  - arau bat theory izan lossless iff it aurresan every observation exactly
  - arau aukeratu the lossless theory of least tamaina
Semantics: linear y = p1 * x + p2 forma; square y = x * x + p2 forma; constant y = p2 forma; mahai y = entry(x) forma.
Smallest lossless theory zer?

ᎠᏙᎩᏯᏍᎩ:
  - theory: theory0, square, 4 ᎠᎴ -1
  - entry: theory1, 3 ᎠᎴ 8
  - theory3 theory size 3
  - entry: theory1, 10 ᎠᎴ 99
  - theory2 theory size 2
  - entry: theory1, 2 ᎠᎴ 3
  - entry: theory1, 12 ᎠᎴ 143
  - theory: theory1, ᎦᏍᎩᎶ, 0 ᎠᎴ 0
  - theory1 theory size 10
  - entry: theory1, 11 ᎠᎴ 120
  - theory0 theory size 2
  - theory: theory3, linear, 7 ᎠᎴ -1
  - theory: theory2, square, 3 ᎠᎴ -3
Data:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ᎦᏍᎩᎶ form y = entry(x).
What smallest lossless theory?

Candidates:
  - theory: theory0, square, 4 -1
  - entry: theory1, 3 8
  - theory3 theory chhika 3
  - entry: theory1, 10 99
  - theory2 theory chhika 2
  - entry: theory1, 2 3
  - entry: theory1, 12 143
  - theory: theory1, patacha, 0 0
  - theory1 theory chhika 10
  - entry: theory1, 11 120
  - theory0 theory chhika 2
  - theory: theory3, linear, 7 -1
  - theory: theory2, square, 3 -3
Data:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Rules:
  - rule theory tiyay lossless iff it predict tukuy observation exactly
  - rule akllay lossless theory of least chhika
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; patacha form y = entry(x).
Smallest lossless theory what?

Candidates:
  - тиориэ: theory0, square, 4 ыкӏи -1
  - entry: theory1, 3 ыкӏи 8
  - theory3 3 тиориэ size
  - entry: theory1, 10 ыкӏи 99
  - theory2 2 тиориэ size
  - entry: theory1, 2 ыкӏи 3
  - entry: theory1, 12 ыкӏи 143
  - тиориэ: theory1, table, 0 ыкӏи 0
  - theory1 10 тиориэ size
  - entry: theory1, 11 ыкӏи 120
  - theory0 2 тиориэ size
  - тиориэ: theory3, linear, 7 ыкӏи -1
  - тиориэ: theory2, square, 3 ыкӏи -3
Data:
  - 3 8 obs
  - 12 143 obs
  - 11 120 obs
  - 2 3 obs
  - 10 99 obs
Rules: rule тиориэ is lossless iff it predict every observation exactly; rule choose the lossless тиориэ of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless тиориэ сыд?

Candidates:
  - theory: theory0, square, 4 thiab -1
  - entry: theory1, 3 thiab 8
  - theory3 theory size 3
  - entry: theory1, 10 thiab 99
  - theory2 theory size 2
  - entry: theory1, 2 thiab 3
  - entry: theory1, 12 thiab 143
  - theory: theory1, rooj, 0 thiab 0
  - theory1 theory size 10
  - entry: theory1, 11 thiab 120
  - theory0 theory size 2
  - theory: theory3, linear, 7 thiab -1
  - theory: theory2, square, 3 thiab -3
Data:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Cai: cai theory is lossless iff nws predict every observation exactly; cai choose lossless theory of least size.
Lub ntsiab: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; rooj form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory0, square, 4 -1
  - entry: theory1, 3 8
  - theory3 theory size 3
  - entry: theory1, 10 99
  - theory2 theory size 2
  - entry: theory1, 2 3
  - entry: theory1, 12 143
  - theory: theory1, table, 0 0
  - theory1 theory size 10
  - entry: theory1, 11 120
  - theory0 theory size 2
  - theory: theory3, linear, 7 -1
  - theory: theory2, square, 3 -3
Data:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of wy krook size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory ining-jak?

Candidates:
  - theory: theory0, square, 4 micha' -1
  - entry: theory1, 3 micha' 8
  - theory3 theory size 3
  - entry: theory1, 10 micha' 99
  - theory2 theory size 2
  - entry: theory1, 2 micha' 3
  - entry: theory1, 12 micha' 143
  - theory: theory1, table, 0 micha' 0
  - theory1 theory size 10
  - entry: theory1, 11 micha' 120
  - theory0 theory size 2
  - theory: theory3, linear, 7 micha' -1
  - theory: theory2, square, 3 micha' -3
Data:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory nanta?

Candidates:
  - theory: theory0, square, 4 カ -1
  - entry: theory1, 3 カ 8
  - theory3 3 theory size
  - entry: theory1, 10 カ 99
  - theory2 2 theory size
  - entry: theory1, 2 カ 3
  - entry: theory1, 12 カ 143
  - theory: theory1, table, 0 カ 0
  - theory1 10 theory size
  - entry: theory1, 11 カ 120
  - theory0 2 theory size
  - theory: theory3, linear, 7 カ -1
  - theory: theory2, square, 3 カ -3
Data:
  - 3 8 obs
  - 12 143 obs
  - 11 120 obs
  - 2 3 obs
  - 10 99 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 ノカ; square y = x * x + p2 ノカ; constant y = p2 ノカ; table y = entry(x) ノカ.
Smallest lossless theory what?

Candidates:
  - theory: theory0, square, 4 ынкъам -1
  - entry: theory1, 3 ынкъам 8
  - theory3 theory size 3
  - entry: theory1, 10 ынкъам 99
  - theory2 theory size 2
  - entry: theory1, 2 ынкъам 3
  - entry: theory1, 12 ынкъам 143
  - theory: theory1, table, 0 ынкъам 0
  - theory1 theory size 10
  - entry: theory1, 11 ынкъам 120
  - theory0 theory size 2
  - theory: theory3, linear, 7 ынкъам -1
  - theory: theory2, square, 3 ынкъам -3
Data:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory0, square, 4 yéetel -1
  - entry: theory1, 3 yéetel 8
  - theory3 theory size 3
  - entry: theory1, 10 yéetel 99
  - theory2 theory size 2
  - entry: theory1, 2 yéetel 3
  - entry: theory1, 12 yéetel 143
  - theory: theory1, table, 0 yéetel 0
  - theory1 theory size 10
  - entry: theory1, 11 yéetel 120
  - theory0 theory size 2
  - theory: theory3, linear, 7 yéetel -1
  - theory: theory2, square, 3 yéetel -3
Data:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Rules:
  - rule theory yan lossless iff it predict every observation exactly
  - rule yéey lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory0, square, 4 -1
  - entry: theory1, 3 8
  - theory3 theory size 3
  - entry: theory1, 10 99
  - theory2 theory size 2
  - entry: theory1, 2 3
  - entry: theory1, 12 143
  - theory: theory1, mę́soną, 0 0
  - theory1 theory size 10
  - entry: theory1, 11 120
  - theory0 theory size 2
  - theory: theory3, linear, 7 -1
  - theory: theory2, square, 3 -3
Data:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Rules:
  - rule theory is lossless iff ą́wąną predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mę́soną form y = entry(x).
Smallest lossless theory híli?

Candidates:
  - theory: theory0, square, 4 na -1
  - entry: theory1, 3 na 8
  - theory3 3 theory size
  - entry: theory1, 10 na 99
  - theory2 2 theory size
  - entry: theory1, 2 na 3
  - entry: theory1, 12 na 143
  - theory: theory1, table, 0 na 0
  - theory1 10 theory size
  - entry: theory1, 11 na 120
  - theory0 2 theory size
  - theory: theory3, linear, 7 na -1
  - theory: theory2, square, 3 na -3
Data:
  - 3 8 obs
  - 12 143 obs
  - 11 120 obs
  - 2 3 obs
  - 10 99 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory0, square, 4 -1
  - entry: theory1, 3 8
  - theory3 theory size 3
  - entry: theory1, 10 99
  - theory2 theory size 2
  - entry: theory1, 2 3
  - entry: theory1, 12 143
  - theory: theory1, table, 0 0
  - theory1 theory size 10
  - entry: theory1, 11 120
  - theory0 theory size 2
  - theory: theory3, linear, 7 -1
  - theory: theory2, square, 3 -3
Data:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory0, square, 4 -1
  - entry: theory1, 3 8
  - theory3 3 theory size
  - entry: theory1, 10 99
  - theory2 2 theory size
  - entry: theory1, 2 3
  - entry: theory1, 12 143
  - theory: theory1, table, 0 0
  - theory1 10 theory size
  - entry: theory1, 11 120
  - theory0 2 theory size
  - theory: theory3, linear, 7 -1
  - theory: theory2, square, 3 -3
Data:
  - 3 8 obs
  - 12 143 obs
  - 11 120 obs
  - 2 3 obs
  - 10 99 obs
Rules:
  - rule maya theory is lossless iff it predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory0, square, 4 ǂʻá -1
  - entry: theory1, 3 ǂʻá 8
  - theory3 theory ʻǁnàhã 3
  - entry: theory1, 10 ǂʻá 99
  - theory2 theory ʻǁnàhã 2
  - entry: theory1, 2 ǂʻá 3
  - entry: theory1, 12 ǂʻá 143
  - theory: theory1, table, 0 ǂʻá 0
  - theory1 theory ʻǁnàhã 10
  - entry: theory1, 11 ǂʻá 120
  - theory0 theory ʻǁnàhã 2
  - theory: theory3, linear, 7 ǂʻá -1
  - theory: theory2, square, 3 ǂʻá -3
Data:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Rules:
  - rule theory ǀîi lossless iff èh predict every observation exactly
  - rule choose lossless theory of least ʻǁnàhã
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory0, square, 4 -1
  - entry: theory1, 3 8
  - theory3 3 theory size
  - entry: theory1, 10 99
  - theory2 2 theory size
  - entry: theory1, 2 3
  - entry: theory1, 12 143
  - theory: theory1, остол, 0 0
  - theory1 10 theory size
  - entry: theory1, 11 120
  - theory0 2 theory size
  - theory: theory3, linear, 7 -1
  - theory: theory2, square, 3 -3
Data:
  - 3 8 obs
  - 12 143 obs
  - 11 120 obs
  - 2 3 obs
  - 10 99 obs
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; остол y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory0, square, 4 -1
  - entry: theory1, 3 8
  - theory3 theory size 3
  - entry: theory1, 10 99
  - theory2 theory size 2
  - entry: theory1, 2 3
  - entry: theory1, 12 143
  - theory: theory1, table, 0 0
  - theory1 theory size 10
  - entry: theory1, 11 120
  - theory0 theory size 2
  - theory: theory3, linear, 7 -1
  - theory: theory2, square, 3 -3
Data:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Rules: rule theory is lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory0, square, 4 -1
  - entry: theory1, 3 8
  - theory3 3 theory size
  - entry: theory1, 10 99
  - theory2 2 theory size
  - entry: theory1, 2 3
  - entry: theory1, 12 143
  - theory: theory1, table, 0 0
  - theory1 10 theory size
  - entry: theory1, 11 120
  - theory0 2 theory size
  - theory: theory3, linear, 7 -1
  - theory: theory2, square, 3 -3
Data:
  - 3 8 obs
  - 12 143 obs
  - 11 120 obs
  - 2 3 obs
  - 10 99 obs
Rules:
  - rule theory is lossless iff kitu predict every observation exactly
  - rule choose lossless theory of least size
Semantics: linear y = p1 * x + p2 form; square y = x * x + p2 form; constant y = p2 form; table y = entry(x) form.
Smallest lossless theory what?

Candidates:
  - theory: theory0, square, 4 -1
  - entry: theory1, 3 8
  - theory3 theory size 3
  - entry: theory1, 10 99
  - theory2 theory size 2
  - entry: theory1, 2 3
  - entry: theory1, 12 143
  - theory: theory1, mesa, 0 0
  - theory1 theory size 10
  - entry: theory1, 11 120
  - theory0 theory size 2
  - theory: theory3, linear, 7 -1
  - theory: theory2, square, 3 -3
Data:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Rules: rule theory is lossless iff it predict every observation exactly; rule choose the lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; mesa form y = entry(x).
Smallest lossless theory what?

Candidates:
  - theory: theory0, square, 4 -1
  - entry: theory1, 3 8
  - theory3 theory size 3
  - entry: theory1, 10 99
  - theory2 theory size 2
  - entry: theory1, 2 3
  - entry: theory1, 12 143
  - theory: theory1, table, 0 0
  - theory1 theory size 10
  - entry: theory1, 11 120
  - theory0 theory size 2
  - theory: theory3, linear, 7 -1
  - theory: theory2, square, 3 -3
Data:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Rules:
  - rule theory nemi lossless iff yaja predict every observation exactly
  - rule choose ne lossless theory of least size
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; ne table form y = entry(x).
Smallest lossless theory tay?

Les candidats sont:
  - théorie: theory0, square, 4 et -1
  - article: theory1, 3 et 8
  - theory3 théorie taille 3
  - article: theory1, 10 et 99
  - theory2 théorie taille 2
  - article: theory1, 2 et 3
  - article: theory1, 12 et 143
  - théorie: theory1, table, 0 et 0
  - theory1 théorie taille 10
  - article: theory1, 11 et 120
  - theory0 théorie taille 2
  - théorie: theory3, linear, 7 et -1
  - théorie: theory2, square, 3 et -3
Les données sont:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Les règles sont:
  - règle un théorie être lossless ssi il prédire tout observation exactement
  - règle choisir le lossless théorie du moindre taille
La sémantique est : linear former y = p1 * x + p2 ; square former y = x * x + p2 ; constant former y = p2 ; la table former y = entry(x).
Quoi smallest lossless théorie ?

Kandidato:
  - teorio: theory0, square, 4 kaj -1
  - entry: theory1, 3 kaj 8
  - theory3 teorio grandeco 3
  - entry: theory1, 10 kaj 99
  - theory2 teorio grandeco 2
  - entry: theory1, 2 kaj 3
  - entry: theory1, 12 kaj 143
  - teorio: theory1, tablo, 0 kaj 0
  - theory1 teorio grandeco 10
  - entry: theory1, 11 kaj 120
  - theory0 teorio grandeco 2
  - teorio: theory3, linear, 7 kaj -1
  - teorio: theory2, square, 3 kaj -3
Datumo:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Regulo: regulo teorio egali lossless iff ĝi predict ĉiu observo ekzakte; regulo elekti lossless teorio de plej malmulta grandeco.
Semantics: linear formi y = p1 * x + p2; square formi y = x * x + p2; constant formi y = p2; tablo formi y = entry(x).
Smallest lossless teorio kio?

Indulók:
  - elmélet: theory0, square, 4 és -1
  - szócikk: theory1, 3 és 8
  - theory3 elmélet méret 3
  - szócikk: theory1, 10 és 99
  - theory2 elmélet méret 2
  - szócikk: theory1, 2 és 3
  - szócikk: theory1, 12 és 143
  - elmélet: theory1, asztal, 0 és 0
  - theory1 elmélet méret 10
  - szócikk: theory1, 11 és 120
  - theory0 elmélet méret 2
  - elmélet: theory3, linear, 7 és -1
  - elmélet: theory2, square, 3 és -3
Adat:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Szabályok:
  - szabály elmélet van veszteségmentes acsa az megjósol minden megfigyelés pontosan
  - szabály kiválaszt a veszteségmentes elmélet of legkisebb méret
Szemantika: linear kialakít y = p1 * x + p2; square kialakít y = x * x + p2; constant kialakít y = p2; a asztal kialakít y = entry(x).
Smallest veszteségmentes elmélet melyik?

候選人:
  - theory:theory0, square, 4及-1
  - entry:theory1, 3及8
  - theory3theory size3
  - entry:theory1, 10及99
  - theory2theory size2
  - entry:theory1, 2及3
  - entry:theory1, 12及143
  - theory:theory1, 檯, 0及0
  - theory1theory size10
  - entry:theory1, 11及120
  - theory0theory size2
  - theory:theory3, linear, 7及-1
  - theory:theory2, square, 3及-3
數據:
  - 3obs8
  - 12obs143
  - 11obs120
  - 2obs3
  - 10obs99
rules:rule:一theory是losslessiffitpredict每observationexactly; rule:揀losslesstheory...嘅leastsize.
semantics:linearformy = p1 * x + p2; squareformy = x * x + p2; constantformy = p2; 檯formy = entry(x).
smallest lossless theory乜嘢?

Candidates:
  - theory: theory0, square, 4 とぅ -1
  - entry: theory1, 3 とぅ 8
  - theory3 theory size 3
  - entry: theory1, 10 とぅ 99
  - theory2 theory size 2
  - entry: theory1, 2 とぅ 3
  - entry: theory1, 12 とぅ 143
  - theory: theory1, table, 0 とぅ 0
  - theory1 theory size 10
  - entry: theory1, 11 とぅ 120
  - theory0 theory size 2
  - theory: theory3, linear, 7 とぅ -1
  - theory: theory2, square, 3 とぅ -3
Data:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Rules: rule theory 有ん lossless iff it predict every observation exactly; rule choose lossless theory of least size.
Semantics: linear form y = p1 * x + p2; square form y = x * x + p2; constant form y = p2; table form y = entry(x).
Smallest lossless theory what?

Үміткер:
  - теория: theory0, square, 4 және -1
  - entry: theory1, 3 және 8
  - theory3 теория мөлшер 3
  - entry: theory1, 10 және 99
  - theory2 теория мөлшер 2
  - entry: theory1, 2 және 3
  - entry: theory1, 12 және 143
  - теория: theory1, үстел, 0 және 0
  - theory1 теория мөлшер 10
  - entry: theory1, 11 және 120
  - theory0 теория мөлшер 2
  - теория: theory3, linear, 7 және -1
  - теория: theory2, square, 3 және -3
Деректер:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
Ереже: ереже теория is lossless iff ол predict әр бақылау exactly; ереже таңдау lossless теория туралы least мөлшер.
Семантикалық: linear пішін y = p1 * x + p2; square пішін y = x * x + p2; constant пішін y = p2; үстел пішін y = entry(x).
Smallest lossless теория не?

מועמדת:
  - תּוֹרָה: theory0, square, 4 וְ־ -1
  - entry: theory1, 3 וְ־ 8
  - theory3 תּוֹרָה גֹּדֶל 3
  - entry: theory1, 10 וְ־ 99
  - theory2 תּוֹרָה גֹּדֶל 2
  - entry: theory1, 2 וְ־ 3
  - entry: theory1, 12 וְ־ 143
  - תּוֹרָה: theory1, טַבְלָה, 0 וְ־ 0
  - theory1 תּוֹרָה גֹּדֶל 10
  - entry: theory1, 11 וְ־ 120
  - theory0 תּוֹרָה גֹּדֶל 2
  - תּוֹרָה: theory3, linear, 7 וְ־ -1
  - תּוֹרָה: theory2, square, 3 וְ־ -3
נְתוּנִים:
  - 3 obs 8
  - 12 obs 143
  - 11 obs 120
  - 2 obs 3
  - 10 obs 99
מָשַׁל:
  - מָשַׁל אַחַת תּוֹרָה הוא lossless אםם זֶה predict כֹּל תַּצְפִּית בדיוק
  - מָשַׁל בחר ה־ lossless תּוֹרָה שֶׁל least גֹּדֶל
תורת המשמעים: linear צורה y = p1 * x + p2; square צורה y = x * x + p2; constant צורה y = p2; טַבְלָה ה־ צורה y = entry(x).
איזה smallest lossless תּוֹרָה?