Tuning the Fuzzy Classification Models with Various Learning Criteria: the Case of Credit Data Classification
Автор
Shtovba, S.
Pankevich, O.
Dounias, G
Штовба, С. Д.
Панкевич, О. Д.
Доуниас, Г.
Дата
2004Metadata
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Анотації
In this paper we study the efficiency of various learning criteria for the
proper tuning of a fuzzy classifier. Different cases of crisp and noisy class borders
are considered, and a specific credit-risk application is discussed.
URI:
http://ir.lib.vntu.edu.ua//handle/123456789/31078