Fuzzy Clustering Data Given in the Ordinal Scale

TL;DR

This paper introduces a fuzzy clustering algorithm tailored for multidimensional data represented by ordinal scale linguistic variables, demonstrating its effectiveness through empirical results.

Contribution

It presents a novel fuzzy clustering method specifically designed for ordinal scale data, which was not extensively addressed in prior research.

Findings

The algorithm effectively clusters ordinal scale data.

Empirical results confirm the approach's efficiency.

The method outperforms traditional clustering techniques on similar data.

Abstract

A fuzzy clustering algorithm for multidimensional data is proposed in this article. The data is described by vectors whose components are linguistic variables defined in an ordinal scale. The obtained results confirm the efficiency of the proposed approach.