A selection model for optimal fuzzy clustering based on hierarchical analytic process
Jiang Hong-feng · Kongzhi yu juece · 2009
Different fuzzy clustering algorithms often generate different fuzzy clusterings over the same data set.Which algorithm can best discover the real structure of the data set is a difficult problem.A selection model for the optimal fuzzy clustering is proposed.This model employs hierarchical analytic process to comprehensively evaluate each alternative fuzzy clustering with multiple cluster validity indexes for fuzzy clusterings and select the optimal one from the alternative fuzzy clusterings.Many experiments show that the optimal fuzzy clustering selected from the alternatives is of the highest pattern recognition rate and perfectly can discover the real structure of the data set.