APPLICATION OF PROBABILISTIC SETS TO FUZZY CLUSTERING.

Witold Pedrycz*, Kaoru Hirota

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

2 Citations (Scopus)

Abstract

Characterization of fuzzy clustering algorithms is dealt with using the concept of probabilistic sets and their subjective entropy. Clustering techniques with objective performance-index criterion-functions are discussed. Several indices characterized by subjective entropy, including indices expressing the degree of interaction between clusters, are proposed. The utility of these indices is illustrated by a simulation method using Iris data and also handwritten-character data.

Original languageEnglish
Title of host publicationAnal of Fuzzy Inf
PublisherCRC Press Inc
Pages169-181
Number of pages13
ISBN (Print)0849362989
Publication statusPublished - 1987

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Pedrycz, W., & Hirota, K. (1987). APPLICATION OF PROBABILISTIC SETS TO FUZZY CLUSTERING. In Anal of Fuzzy Inf (pp. 169-181). CRC Press Inc.