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7. A Novel Alternative Weighted Fuzzy C-Means Algorithm and Cluster Validity Analysis

Author

Gao Xiaoying, Guo Rui, Wang Lina, Zhang Chi, Liu Zhiying, Zuo Ke, Wang Xiang, Lei Wei, and Liu Jizhong

Subjects
Metric space, Statistical classification, Fuzzy clustering, k-medoids, Algorithm design, Cluster analysis, Fuzzy logic, Algorithm, k-medians clustering, Mathematics
Abstract

Proposed a novel fuzzy cluster algorithm-AWFCM, aiming at large miss-clustering and invalidation in the fuzzy C-means algorithm when has noises and uneven samples situation. This new algorithm defined a new distance in new metric space and introduced weight matrix based on sample dots' density. New definition of distance can efficiently restrain the error range of clustering centers for samples with noise points in iteration, meanwhile improve recursion for clustering centers according to samples' density. Experiments have proved that AWFCM algorithm overcomes bugs of FCM algorithm to a certain extent, with favorable convergence and robust.

Published
2008

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