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

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.