Generating Weighted Fuzzy Rules From Training Data for Handling Fuzzy Classification Problems

Abstract

In this paper, we present a new algorithm to generate weighted fuzzy rules from a set of training data, where the attributes appearing in the antecedent parts of the generated fuzzy rules may have different weights. We also apply the generated weighted fuzzy rules to deal with the "Saturday Morning Problem", where the proposed algorithm can obtain a higher classification accuracy rate and generate less fuzzy rules than the existing methods.