A Generalization of Gustafson-Kessel Algorithm Using a New Constraint Parameter

TL;DR

This paper introduces a generalized fuzzy clustering algorithm that extends Gustafson-Kessel by incorporating a new constraint parameter, enhancing flexibility in clustering based on a dissimilarity function.

Contribution

The paper proposes a novel fuzzy clustering algorithm that generalizes Gustafson-Kessel through a new constraint parameter, allowing more adaptable clustering.

Findings

Demonstrates improved clustering flexibility

Provides a new dissimilarity function framework

Extends Gustafson-Kessel algorithm capabilities

Abstract

In this paper one presents a new fuzzy clustering algorithm based on a dissimilarity function determined by three parameters. This algorithm can be considered a generalization of the Gustafson-Kessel algorithm for fuzzy clustering.