On the extension of fuzzy k-means algorithms for detection of linear clusters

Abstract

In this note we discuss an extension of the fuzzy ISODATA (or fuzzy k-means) clustering algorithms, which attempt to recognize and compensate for their failure at detection of linear substructure in finite data sets. A numerical example is given to substantiate the proposed extension: and we offer some theoretical conjectures concerning its construction.