Genetic fuzzy clustering by means of discovering membership functions
ADVANCES IN INTELLIGENT DATA ANALYSIS, cilt.1280, ss.383-393, 1997 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 1280
- Basım Tarihi: 1997
- Dergi Adı: ADVANCES IN INTELLIGENT DATA ANALYSIS
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, EMBASE, MathSciNet, Philosopher's Index, zbMATH
- Sayfa Sayıları: ss.383-393
- Orta Doğu Teknik Üniversitesi Adresli: Hayır
Özet
It has been observed that in the previous Genetic Algorithms (GA) based Fuzzy Clustering (FC) works only some of the parameters of an FC system are developed. Here, a new approach is proposed to develop directly the membership functions for the clusters using GA. This new technique is implemented and tested on common test data. A comparative study of the results against the quotations in literature reveals that the standard c-means FC technique is outperformed by the proposed technique in the count of misclassifications aspect.