Incremental Refinement of Approximate Domain Theories

Ronen Feldman, Alberto Segre, Moshe Koppel

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

In this paper we present a framework for performing incremental correction of approximate domain theories. Approximate domain theories are domain theories which are incomplete and/or incorrect. Based on initial information, belief values are assigned to different subsets of each clause in the domain theory. These belief values provide bias towards the correct refinement of the domain theory. We provide an incremental algorithm that refines the domain theory after observing positive and negative exemplars. Our algorithm requires a smaller number of misclassified exemplars than other algorithms presented in the literature.

Original languageAmerican English
Title of host publicationProceedings of the 8th International Workshop on Machine Learning, ICML 1991
EditorsLawrence A. Birnbaum, Gregg C. Collins
PublisherMorgan Kaufmann Publishers, Inc.
Pages500-504
Number of pages5
ISBN (Electronic)1558602003, 9781558602007
DOIs
StatePublished - 1991
Externally publishedYes
Event8th International Workshop on Machine Learning, ICML 1991 - Evanston, United States
Duration: 1 Jun 1991 → …

Publication series

NameProceedings of the 8th International Workshop on Machine Learning, ICML 1991

Conference

Conference8th International Workshop on Machine Learning, ICML 1991
Country/TerritoryUnited States
CityEvanston
Period1/06/91 → …

Bibliographical note

Publisher Copyright:
© ICML 1989.All rights reserved

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