Proceedings of the Korean Institute of Intelligent Systems Conference (한국지능시스템학회:학술대회논문집)

Korean Institute of Intelligent Systems (한국지능시스템학회)
권호 표지

A Construction of Fuzzy Model for Data Mining

데이터 마이닝을 위한 퍼지 모델 동정

  • Kim, Do-Wan (Department of Electronic Eng., Yonsei Univ) ;
  • Park, Jin-Bae (Department of Electronic Eng., Yonsei Univ) ;
  • Kim, Jung-Chan (School of Electronic and Information Eng., Kunsan National Univ) ;
  • Joo, Young-Hoon (School of Electronic and Information Eng., Kunsan National Univ)
  • Published : 2002.12.01

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Abstract

In this paper, a new GA-based methodology with information granules is suggested for construction of the fuzzy classifier. We deal with the selection of the fuzzy region as well as two major classification problems-the feature selection and the pattern classification. The proposed method consists of three steps: the selection of the fuzzy region, the construction of the fuzzy sets, and the tuning of the fuzzy rules. The genetic algorithms (GAs) are applied to the development of the information granules so as to decide the satisfactory fuzzy regions. Finally, the GAs are also applied to the tuning procedure of the fuzzy rules in terms of the management of the misclassified data (e.g., data with the strange pattern or on the boundaries of the classes). To show the effectiveness of the proposed method, an example-the classification of the Iris data, is provided.

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