Fuzzy Adaptive Resonance Theory, Diffusion Maps and their applications to Clustering and Biclustering
arXiv:1411.5737v56 citations
Originality Synthesis-oriented
AI Analysis
This work addresses clustering challenges in high-dimensional data analysis, but it appears incremental as it hybridizes existing methods without claiming major breakthroughs.
The paper introduces FARDiff, an algorithm that combines Diffusion Maps and Fuzzy Adaptive Resonance Theory for clustering high-dimensional data, and discusses its applications and future research directions.
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.