Rule simplification

Eyal Kolman; Michael Margaliot

doi:10.1007/978-3-540-88077-6_4

Rule simplification

Eyal Kolman^*, Michael Margaliot

^*Corresponding author for this work

School of Electrical Engineering

Tel Aviv University

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

The interpretability of FRBs might be hampered by the existence of a large number of rules or complicated ones. Thus, any attempt to use the FARB-ANN equivalence for knowledge extraction from large-scale networks must include a systematic approach for rule reduction and simplification. Simplification procedures usually lead to a more interpretable rule-base with the cost of a degradation in the FRB performance. This tradeoff between complexity and interpretability can be viewed as one manifestation of Zadeh's principle of incompatibility (see Section 1.2).

Original language	English
Title of host publication	Knowledge-Based Neurocomputing
Subtitle of host publication	A Fuzzy Logic Approach
Editors	Eyal Kolman, Michael Margaliot
Publisher	Springer Berlin Heidelberg
Pages	37-40
Number of pages	4
ISBN (Print)	9783540880769
DOIs	https://doi.org/10.1007/978-3-540-88077-6_4
State	Published - 2009

Publication series

Name	Studies in Fuzziness and Soft Computing
Volume	234
ISSN (Print)	1434-9922

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Rule simplification

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