TY - GEN

T1 - Uniform characterizations of Polynomial-Query learnabilities

AU - Hayashi, Yosuke

AU - Matsumoto, Satoshi

AU - Shinohara, Ayumi

AU - Takeda, Masayuki

N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 1998.

PY - 1998

Y1 - 1998

N2 - We consider the exact learning in the query model. We deal with all types of queries introduced by Angluin: membership, equivalence, superset, subset, disjointness and exhaustiveness queries, and their weak (or restricted) versions where no counterexample is returned. For each of all possible combinations of these queries, we uniformly give complete characterizations of boolean concept classes that are learnable using a polynomial number of polynomial sized queries. Our characterizations show the equivalence between the learnability of a concept class C using queries and the existence of a good query for any subset H of C which is guaranteed to reject a certain fraction of candidate concepts in H regardless of the answer. As a special case for equivalence queries alone, our characterizations directly correspond to the lack of the approximate fingerprint property, which is known to be a sufficient and necessary condition for the learnability using equivalence queries.

AB - We consider the exact learning in the query model. We deal with all types of queries introduced by Angluin: membership, equivalence, superset, subset, disjointness and exhaustiveness queries, and their weak (or restricted) versions where no counterexample is returned. For each of all possible combinations of these queries, we uniformly give complete characterizations of boolean concept classes that are learnable using a polynomial number of polynomial sized queries. Our characterizations show the equivalence between the learnability of a concept class C using queries and the existence of a good query for any subset H of C which is guaranteed to reject a certain fraction of candidate concepts in H regardless of the answer. As a special case for equivalence queries alone, our characterizations directly correspond to the lack of the approximate fingerprint property, which is known to be a sufficient and necessary condition for the learnability using equivalence queries.

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U2 - 10.1007/3-540-49292-5_8

DO - 10.1007/3-540-49292-5_8

M3 - Conference contribution

AN - SCOPUS:84949211417

SN - 3540653902

SN - 9783540653905

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 84

EP - 92

BT - Discovery Science - 1st International Conference, DS 1998, Proceedings

A2 - Arikawa, Setsuo

A2 - Motoda, Hiroshi

PB - Springer Verlag

T2 - 1st International Conference on Discovery Science, DS 1998

Y2 - 14 December 1998 through 16 December 1998

ER -