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Abstract: For complex and high-dimensional problems, data-driven identification of classifiers has to deal with structural issues like the selection of the relevant features and effective initial partition of the input domain. Therefore, the identification of fuzzy classifiers is a challenging topic. Decision-tree (DT) generation algorithms are effective in feature selection and extraction of crisp classification rules, hence they can be used for the initialization of fuzzy systems. Because fuzzy... (Update)
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BibTeX entry: (Update)
@misc{ abonyi-structure,
author = "Janos Abonyi and Hans Roubos",
title = "Structure Identification of Fuzzy Classifiers",
url = "citeseer.ist.psu.edu/abonyi00structure.html" }
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