Feature weighting and feature selection in fuzzy clustering

Abstract

This paper studies the problem of weighting and selecting attributes and principal axes in fuzzy clustering. Its main contribution is a selection method that is not based on simply applying a threshold to computed feature weights, but directly assigns zero weights to features that are not informative enough. This has the important advantage that the clustering result that can be obtained on the selected subspace coincides with the projection (to the selected subspace) of the clustering result that is obtained on the full data space.