Fuzzy Adaptive Resonance Theory, Diffusion Maps and their applications to Clustering and Biclustering

TL;DR

This paper introduces FARDiff, an algorithm combining Diffusion Maps and Fuzzy Adaptive Resonance Theory for clustering high-dimensional data, with applications and future research directions.

Contribution

The paper presents a novel algorithm that integrates Diffusion Maps and Fuzzy ART for improved clustering of high-dimensional datasets.

Findings

Effective clustering on high-dimensional data demonstrated

Applications in various domains showcased the method's versatility

Identified challenges and future research directions

Abstract

In this paper, we describe an algorithm FARDiff (Fuzzy Adaptive Resonance Dif- fusion) which combines Diffusion Maps and Fuzzy Adaptive Resonance Theory to do clustering on high dimensional data. We describe some applications of this method and some problems for future research.