Voting in fuzzy rule-based systems for pattern classification problems

doi:10.1016/S0165-0114(98)00223-1

1999-04-01

176

PRE

Hisao Ishibuchi *

Tomoharu Nakashima

T. Morisawa

DOI：10.1016/S0165-0114(98)00223-1

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摘要

En 中文

In this paper, we examine two kinds of voting schemes in fuzzy rule-based systems for pattern classification problems. One is the voting by multiple fuzzy if-then rules in a single fuzzy rule-based classification system. The other is the voting by multiple fuzzy rule-based classification systems. First, we discuss the voting by multiple fuzzy if-then rules, which is used as a fuzzy reasoning method for classifying input patterns in a single fuzzy rule-based classification system. The performance of the voting by multiple fuzzy if-then rules is examined by computer simulations on the iris data. Next, we discuss the voting by multiple fuzzy rule-based classification systems. Three voting methods (i.e., a perfect unison rule, a majority rule, and a weighted voting rule) are used for combining classification results by multiple fuzzy mle-based classification systems. Finally, we compare the performance of fuzzy rule-based classification systems with that of other classification methods such as neural networks and statistical techniques by computer simulations on some well-known test problems. (C) 1999 Elsevier Science B.V. All rights reserved.

Keyword:

pattern classification

fuzzy rule-based systems

fuzzy reasoning

voting schemes