On Some Fuzzy Clustering Algorithms with Dimensionality Reduction

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.