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Subjective Entropy of Probabilistic Sets and Fuzzy Cluster Analysis

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2 Author(s)
Hirota, K. ; Department of Instrument and Control Engineering, College of Engineering, Hosei University, Kajino-cho 3-7-2, Koganei-city, Tokyo 184, Japan ; Pedrycz, W.

The results of different fuzzy clustering algorithms are dealt with collectively in a formal framework of probabilistic set theory in order to interpret the structure of data. Special attention is paid to calculation of entropy of the fuzzy clusters detected by various grouping methods. Two numerical examples illustrate applicability of the proposed way of cluster evaluation.

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Systems, Man and Cybernetics, IEEE Transactions on  (Volume:16 ,  Issue: 1 )