Machine Learning

, Volume 2, Issue 4, pp 319–342

Queries and Concept Learning

  • Dana Angluin
Article

DOI: 10.1023/A:1022821128753

Cite this article as:
Angluin, D. Machine Learning (1988) 2: 319. doi:10.1023/A:1022821128753
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Abstract

We consider the problem of using queries to learn an unknown concept. Several types of queries are described and studied: membership, equivalence, subset, superset, disjointness, and exhaustiveness queries. Examples are given of efficient learning methods using various subsets of these queries for formal domains, including the regular languages, restricted classes of context-free languages, the pattern languages, and restricted types of prepositional formulas. Some general lower bound techniques are given. Equivalence queries are compared with Valiant's criterion of probably approximately correct identification under random sampling.

Concept learning supervised learning queries 

Copyright information

© Kluwer Academic Publishers 1988

Authors and Affiliations

  • Dana Angluin
    • 1
  1. 1.Department of Computer ScienceYale University, P.O. BoxNew HavenUSA

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