Proceedings of the Fuzzy System Symposium
38th Fuzzy System Symposium
Session ID : TD2-2
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On Some Fuzzy Clustering Algorithms with Dimensionality Reduction
*Masanori KawamuraYuchi Kanzawa
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Abstract

There are some variants of fuzzification technique in Fuzzy c-means, such as Bezdek-type, KL-divergence-regularized type, q-divergence-based type, and some fuzzy clustering algorithms with di- mensionality reduction methods have been proposed. However, not all these combinations have been proposed. There is a potential to increase clustering accuracy by variously combinig a fuzzification tech- nique and a dimensionality reduction method. In this report, eleven fuzzy clustering algorithms are pro- posed based on some dimensionality reduction methods, and the proposed methods are compared in terms of accuracy.

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© 2022 Japan Society for Fuzzy Theory and Intelligent Informatics
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