On the sample complexity of consistent learning with one-sided error

Eiji Takimoto, Akira Maruoka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Although consistent learning is sufficient for PAC-learning, it has not been found what strategy makes learning more efficient, especially on the sample complexity, i.e., the number of examples required. For the first step towards this problem, only classes that have consistent learning algorithms with one-sided error are considered. A combinatorial quantity called maximal particle sets is introduced, and an upper bound of the sample complexity of consistent learning with one-sided error is obtained in terms of maximal particle sets. For the class of n-dimensional parallel axis rectangles, one of those classes that are consistently learnable with one-sided error, the cardinality of the maximal particle set is estimated and (Formula Found) upper bound of the learning algorithm for the class is obtained. This bound improves the bounds due to Blumer et al. [2] and meets the lower bound within a constant factor.

Original languageEnglish
Title of host publicationAlgorithmic Learning Theory - 4th International Workshop, ALT 1993, Proceedings
EditorsKlaus P. Jantke, Shigenobu Kobayashi, Etsuji Tomita, Takashi Yokomori
PublisherSpringer Verlag
Pages265-278
Number of pages14
ISBN (Print)9783540573708
Publication statusPublished - Jan 1 1993
Externally publishedYes
Event4th Workshop on Algorithmic Learning Theory, ALT 1993 - Tokyo, Japan
Duration: Nov 8 1993Nov 10 1993

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume744 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other4th Workshop on Algorithmic Learning Theory, ALT 1993
CountryJapan
CityTokyo
Period11/8/9311/10/93

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All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Takimoto, E., & Maruoka, A. (1993). On the sample complexity of consistent learning with one-sided error. In K. P. Jantke, S. Kobayashi, E. Tomita, & T. Yokomori (Eds.), Algorithmic Learning Theory - 4th International Workshop, ALT 1993, Proceedings (pp. 265-278). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 744 LNAI). Springer Verlag.