ISO-2382-31-1997.pdf

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1、INTERNATIONAL STANDARD NORME INTERNATIONALE ISO/IEC 2382-31 First edition Premihre bdition 1997-12-15 Information technology - Vocabulary - Part 31: Artificial intelligence - Machine learning Technologies de I information - Vocabulaire - Partie 31: Intelligence artificielle - Apprentissage automatiq

2、ue Reference number Numbro de rbfbrence ISO/I EC 2382-31: 1997( E/F) Copyright International Organization for Standardization Provided by IHS under license with ISO Licensee=NASA Technical Standards 1/9972545001 Not for Resale, 04/17/2007 19:49:32 MDTNo reproduction or networking permitted without l

3、icense from IHS -,-,- lSO/IEC 2382-31 : 1997 (E/F) Contents Foreword Introduction Page iv vi Section 1: General 1.1 Scope 1.2 Normative references 1.3 Principles and rules followed 1.3.1 Definition of an entry 1.3.2 Organization of an entry 1.3.3 Classification of entries 1.3.4 Selection of terms an

4、d wording of definitions 1.3.5 Multiple meanings 1.3.6 Abbreviations 1.3.7 Use of parentheses 1.3.8 Use of brackets 1.3.9 Use of terms printed in italic typeface in definitions and the use of an asterisk 1.3.10 Spelling a .3.11 Organization of the alphabetical index Section 2: Terms and definitions

5、31 Artificial intelligence - Machine learning 31 .Ol General concepts 31.02 Learning techniques 31.03 Learning strategies Alphabetical indexes English French 0 ISO/IEC 1997 All rights reserved. Unless otherwise specified, no part of this publication may be reproduced or utilized In any form or by an

6、y means, electronic or mechanrcai, Including photocopying and microfilm, without permission in wntrng from the publrsher. / Droits de reproduction reserves. Sauf prescription differente, aucune parrre de cette publication ne peut etre reproduite nl utilisee sous quelque forme que ce soit et par aucu

7、n procede, electronrque ou mecanique, y compns la photocople et les mrcrofilms, sans I accord ecrit de I edlteur. lSO/IEC Copyright Office 0 Case postale 56 l Cl-I-1 211 Geneve 20 0 Switzerland 4 4 4 5 5 9 13 15 Pnnted In Switzeriand/lmpnme en Sulsse ii Copyright International Organization for Stand

8、ardization Provided by IHS under license with ISO Licensee=NASA Technical Standards 1/9972545001 Not for Resale, 04/17/2007 19:49:32 MDTNo reproduction or networking permitted without license from IHS -,-,- 0 ISOAEC ISOAEC 2382-31 : 1997 (E/F) Sommaire Page Avant-propos . V Introduction vii Section

9、1: Gkrkalitks 1.1 Domaine d application . . 1 1.2 References normatives . 1 1.3 Principes d etablissement et regles suivies 2 1.3.1 1.3.2 1.3.3 1.3.4 1.3.5 1.3.6 1.3.7 1.3.8 1.3.9 1.3.10 1.3.11 Definition de I article . 2 Constitution d un article 2 Classification des articles . 3 Choix des termes e

10、t des definitions . 3 Pluralite de sens ou polysemie . 3 Abreviations . 3 Emploi des parentheses . 3 Emploi des crochets . 4 Emploi dans les definitions de termes imprimes en caracteres italiques et de I asterisque . 4 Mode d ecriture et orthographe . 4 Constitution de I index alphabetique 4 Section

11、 2: Termes et dkfinitions 31 Intelligence artificielle - Apprentissage automatique 5 31 .Ol Notions get a) un numero de reference (le meme, quelle que soit la langue de publication de la presente par-tie de l ISO/CEI 2382) ; b) the term or the generally preferred term in the language. The absence of

12、 a generally preferred term for the concept in the language is indicated by a symbol consisting of five dots (.); a row of dots may be used to indicate, in a term, a word to be chosen in each particular case; b) le terme, ou le terme prefer-e en general dans la langue. L absence, dans une langue, de

13、 terme consacre ou a conseiller pour exprimer une notion est indiquee par un symbole consistant en cinq points de suspension (.) ; les points de suspension peuvent etre employ c) the preferred term in a particular accord ing to the rules of IS0 3166); country (identified c) le terme prefer-e dans un

14、 certain pays (identifie selon les regles de I ISO 3166) ; d) the abbreviation for the term; d) I abreviation pouvant etre employee a la place du terme ; e) permitted synonymous term(s); e) le terme ou les termes admis comme synonymes ; f) the text of the definition (see 1.3.4); f) le texte de la de

15、finition (voir 1.3.4) ; g) one or more examples with the heading “Example(s)“; s ) est emprunte 8 la genetique des especes naturelles avec ses connotations d heredite, de variation des especes et de persistance du plus apte. 12 Copyright International Organization for Standardization Provided by IHS

16、 under license with ISO Licensee=NASA Technical Standards 1/9972545001 Not for Resale, 04/17/2007 19:49:32 MDTNo reproduction or networking permitted without license from IHS -,-,- 0 ISOAEC ISOIIEC 2382-31 : 1997 (E/F) Alphabetical index acquisition adaptive advice analogy analysis analytic assignme

17、nt associative automatic being case-based causal , characteristic chunking clustering cognitive cognitivism complete concept conceptual confusion consistent constraint-based credit/blame deduction deductive description discovery discriminant doing example example-based A knowledge acquisition . 31.0

18、1.04 adaptive learning . 31.03.02 advice taking . 31.03.06 learning by analogy . 31.03.20 causal analysis . 31.03.01 analytic learning 31.03.18 credit/blame assignment . 31.03.21 associative learning 31.03.20 automatic learning 31.01.02 B learning by being told 31.03.05 C case-based learning . 30.03

19、.16 causal analysis . 31.03.01 characteristic description 31.02.04 chunking . 31.02.03 conceptual clustering 31.01.08 cognitive science 31 .Ol .I 1 cognitivism 31 .Ol .l 1 complete generalization 31.02.16 concept . 31.01.06 concept learning . 31.01.07 concept description 31.02.02 concept formation .

20、 31.02.07 partially learned concept . 31.02.08 concept generalization 31.02.12 concept specialization 31.02.17 concept validation . 31.02.19 conceptual clustering 31.01.08 confusion matrix . 31.02.18 consistent generalization 31.02.13 constraint-based generalization . .31 .02.14 credit/blame assignm

21、ent . 31.03.21 D learning by deduction 31.03.17 deductive learning . 31.03.17 concept description 31.02.02 characteristic description 31.02.04 discriminant description 31.02.05 structural description 31.02.06 description space . 31.02.11 machine discovery 31 .Ol .I 0 learning by discovery 31.03.10 d

22、iscriminant description 31.02.05 learning while doing 31.03.25 E example space 31.02.10 learning from examples 31.03.12 positive example . 31.03.13 negative example 31.03.14 example-based learning 31.03.12 explanation-based explanation-based learning . . . . . . . . . . . . . . . . . . . . . . .31.0

23、3.18 formation taxonomy formation 31.01.09 concept formation 31.02.07 G generalization genetic concept generalization . 31.02.12 consistent generalization 31.02.13 constraint-based generalization .31.02.14 similarity-based generalization .31.02.15 complete generalization 31.02.16 genetic learning 31

24、.03.26 H heuristic heuristic learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.03.04 I incremental induction inductive instance instance-based instruction incremental learning . 31.03.07 learning by induction 31.03.11 inductive learning . 31.03.11 instance space

25、 . 31.02.10 positive instance 31.03.13 negative instance . 31.03.14 instance-based learning . 31.03.12 learning from instruction 31.03.05 K knowledge knowledge acquisition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 .01.04 L learned learning partially learned concept 31.02.08 lear

26、ning 31 .Ol .Ol machine learning 31.01.02 automatic learning 31.01.02 learning strategy . 31.01.05 concept learning . 31.01.07 rote learning . 31.03.02 adaptive learning 31.03.02 heuristic learning 31.03.04 learning by being told . 31.03.05 learning from instruction 31.03.05 incremental learning . 3

27、1.03.07 supervised learning 31.03.08 unsupervised learning 31.03.09 learning without a teacher . .31.03.09 learning by discovery 31.03.10 learning from observation .31 .03.10 inductive learning . 31.03.11 learning by induction 31.03.11 learning from examples 31.03.12 example-based learning . 31.03.1

28、2 instance-based learning . 31.03.12 case-based learning . 31.03.16 deductive learning 31.03.17 learning by deduction . 31.03.1.7 analytic learning . 31.03.18 explanation-based learning . .31.03.18 F Copyright International Organization for Standardization Provided by IHS under license with ISO Lice

29、nsee=NASA Technical Standards 1/9972545001 Not for Resale, 04/17/2007 19:49:32 MDTNo reproduction or networking permitted without license from IHS -,-,- ISO/IEC 2382-31:1997 (E/F) OISOAEC learning by analogy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.03.19 associative l

30、earning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.03.19 reinforcement learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.03.22 learning from solution paths . . . . . . . . . . . . . . . . . . . . . 31.03.23 learning while doing . . . . . . . . . . .

31、. . . . . . . . . . . . . . . . . . . . . . . 31.03.25 genetic learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.03.26 learning-apprentice validation version V concept validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.02.1

32、9 version space . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.02.09 learning-apprentice strategy . . . . . . . . . . . . . . . . . . . . .31 .03.24 M machine matrix machine learning 31.01.02 machine discovery 31 .Ol .I0 confusion matrix . 31.02.18 N near-mi

33、ss negative near-miss . 31.03.15 negative example 31.03.14 negative instance 31.03.14 0 observation learning from observation . 31.03.10 operationalization operationalization . . . . . . . . . . . . . . 31.03.19 partially paths positive reinforcement rote science self-learning similarity-based solut

34、ion space specialization strategy structural supervised taking advice taking . 31.03.06 taxonomy taxonomy formation 31.01.09 teacher learning without a teacher .31 .03.09 told learning by being told 31.03.05 unlearning unlearning . 31.02.01 unsupervised unsupervised learning 31.03.09 P partially lea

35、rned concept . 31.02.08 learning from solution paths .31 .03.23 positive example . 31.03-l 3 positive instance . 31.03.13 reinforcement rote learning . learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .31.03.22 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

36、 . . . . . . . 31.03.02 S cognitive science 31 .Ol .I 1 self-learning 31.01.03 similarity-based generalization . .31.02.15 learning from solution paths .31.03.23 version space . 31.02.09 instance space . 31.02.10 example space 31.02.10 description space . 31.02.11 concept specialization 31.02.17 lea

37、rning strategy . 31.01.05 learning-apprentice strategy .31.03.24 structural description 31.02.06 supervised learning 31.03.08 T U 14 Copyright International Organization for Standardization Provided by IHS under license with ISO Licensee=NASA Technical Standards 1/9972545001 Not for Resale, 04/17/20

38、07 19:49:32 MDTNo reproduction or networking permitted without license from IHS -,-,- o ISOAEC ISOAEC 2382-31 x 1997 (E/F) Index Alphabktique A D acquisition des connaissances .31 .Ol .04 apprentissage adaptatif 31.03.02 agregation conceptuelle 31.01.08 apprentissage par analogie .31.03.20 analyse c

39、ausale 31.03.01 apprentissage analytique 31.03.18 strategie de I apprenti 31.03.24 apprentissage . 31 .Ol .Ol apprentissage automatique .31.01.02 apprentissage machine 31.01.02 strategie d apprentissage . .3l .Ol .05 apprentissage de concept . .31 .01.07 apprentissage par memorisation .31 .03.02 app

40、rentissage adaptatif . .31.03.02 apprentissage heuristique . .31 .03.04 apprentissage par instruction .31.03.05 apprentissage par consultation .31.03.06 apprentissage incremental . .31.03.07 apprentissage incrementiel .31.03.07 apprentissage supervise . 31.03.08 apprentissage non supervise . .31.03.

41、09 apprentissage par decouverte . .31 .03.10 apprentissage par observation . .31 .03.10 apprentissage inductif . .31 .03.1 1 apprentissage par exemples .31.03.12 apprentissage par cas . -31 .03.16 apprentissage deductif . 31.03.17 apprentissage analytique . .31.03.18 apprentissage par analogie .31 .

42、03.20 apprentissage associatif . 31.03.20 apprentissage par renforcement .31 .03.22 apprentissage par voies de resolution 31.03.2 3 apprentissage par la pratique .31 .03.25 apprentissage genetique 31.03.26 apprentissage associatif .31 .03.20 attribution de credit-blame . .31 .03.21 attribution de re

43、compense-punition .31 .03.21 decouverte deductif desapprentissage description decouverte par la machine .31 .Ol .I 0 apprentissage par decouverte . .31 .03.10 apprentissage deductif . 31.03.17 desapprentissage . 31.02.01 description de concept . 31.02.02 description par traits distinctifs . .31.02.0

44、4 description par dissimilarites . .31 .02.05 description structurale 31.02.06 espace de descriptions 31.02.11 description par dissimilarites 31 .02.05 description par traits distinctifs . .31 .02.04 acquisition adaptatif agregation analogie analyse analytique apprenti apprentissage associatif attri

45、bution issimilarites istinctifs E espace de versions . .31 .02.09 espace d instances . .31 .02.10 espace d exemples .31 .02.10 espace de descriptions . .31.02.11 exemple positif .31.03.13 exemple negatif 31.03.14 espace d exemples .31.02.10 apprentissage par exemples . .31 -03.12 espace exemple exem

46、ples F formation taxinomique 31.01.09 formation de concept . 31.02.07 formation G generalisation de concept . .31 .02.12 generalisation consistante . .31.02.13 generalisation par contraintes . .31.02.14 generalisation par similarites 31 .02.15 generalisation complete . 31.02.16 apprentissage genetiq

47、ue 31.03.26 grille de correction . .31 .02.18 generalisation auto-apprentissage auto-apprentissage . 31.01.03 apprentissage automatique .31 .Ol .02 C apprentissage par cas 31.03.16 analyse causale 31.03.01 science cognitive 31 .Ol .I 1 cognitivisme 31 .Ol .I 1 generalisation complete 31.02.16 concep

48、t . 31.01.06 apprentissage de concept . .31 .01.07 description de concept .31 .02.02 formation de concept 31.02.07 concept appris partiellement .31 .02.08 generalisation de concept .31.02.12 specialisation d un concept .31 .02.17 validation de concept 31.02.19 agregation conceptuelle 31.01.08 matric

49、e de confusion 31.02.18 acquisition des connaissances .31 .Ol .04 generalisation consistante . .31 .02.13 apprentissage par consultation .31 .03.06 generalisation par contraintes . 31.02.14 grille de correction 31.02.18 attribution de credit-blame . .31.03.21 genetique grille automatique cas causale cognitive cognitivisme complete concept conceptuelle confu