Entropy-weighted medoid shift: An automated clustering algorithm for high-dimensional data

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Abhishek Kumar, Oladayo S. Ajani, Swagatam Das, Rammohan Mallipeddi

Published: 2025, Last Modified: 28 Sept 2025Appl. Soft Comput. 2025EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Highlights•Novel mode-seeking algorithm for clustering high-dimensional datasets in projected subspaces.•Subspace-determining scheme enhances accuracy of cluster identification.•Guaranteed convergence without stopping criteria in the proposed algorithm.•Experimental studies show effectiveness against state-of-the-art algorithms in high-dimensional environments with high noise-to-signal ratio.