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- Sample_exclusion_dimension abstract "In computational learning theory, sample exclusion dimensions arise in the study of exact concept learning with queries.In algorithmic learning theory, a concept over a domain X is a Boolean function over X. Here we only consider finite domains. A partial approximation S of a concept c is a Boolean function over such that c is an extension to S.Let C be a class of concepts and c be a concept (not necessarily in C). Then a specifying set for c w.r.t. C, denoted by S is a partial approximation S of c such that C contains at most one extension to S. If we have observed a specifying set for some concept w.r.t. C, then we have enough information to verify a concept in C with at most one more mind change.The exclusion dimension, denoted by XD(C), of a concept class is the maximum of the size of the minimum specifying set of c' with respect to C, where c' is a concept not in C.".
- Sample_exclusion_dimension wikiPageID "3119343".
- Sample_exclusion_dimension wikiPageRevisionID "573837507".
- Sample_exclusion_dimension hasPhotoCollection Sample_exclusion_dimension.
- Sample_exclusion_dimension subject Category:Computational_learning_theory.
- Sample_exclusion_dimension comment "In computational learning theory, sample exclusion dimensions arise in the study of exact concept learning with queries.In algorithmic learning theory, a concept over a domain X is a Boolean function over X. Here we only consider finite domains. A partial approximation S of a concept c is a Boolean function over such that c is an extension to S.Let C be a class of concepts and c be a concept (not necessarily in C). Then a specifying set for c w.r.t.".
- Sample_exclusion_dimension label "Sample exclusion dimension".
- Sample_exclusion_dimension sameAs m.08spbs.
- Sample_exclusion_dimension sameAs Q7410136.
- Sample_exclusion_dimension sameAs Q7410136.
- Sample_exclusion_dimension wasDerivedFrom Sample_exclusion_dimension?oldid=573837507.
- Sample_exclusion_dimension isPrimaryTopicOf Sample_exclusion_dimension.