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The use of Bayesian Network Classifiers (BCs) combined with the Fuzzy rule model to explain the learned BCs have been previously presented as the BayesFuzzy approach. This paper follows along BayesFuzzy lines of investigation aiming at improving the comprehensibility of a BC model and enhancing BayesFuzzy results by combining new pruning methods. In order to improve BayesFuzzy performance, in addition...
The definition of the fuzzy rule base is one of the most important and difficult tasks when designing fuzzy systems. This paper discusses the results of two different hybrid methods investigated earlier, for the automatic generation of fuzzy rules from numerical data. One of the methods proposes the creation of fuzzy rule bases using genetic algorithms in association with a heuristic for preselecting...
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