Tsallis Entropy-Regularized Fuzzy Classification Maximum Likelihood Clustering with a t-Distribution

• Published in: Journal of Advanced Computational Intelligence and Intelligent Informatics Vol. 29; no. 2; pp. 365 - 378
• Main Authors: Suzuki, Yuta, Kanzawa, Yuchi
• Format: Journal Article
• Language: English
• Published: Tokyo Fuji Technology Press Ltd 20.03.2025; 富士技術出版株式会社; Fuji Technology Press Co. Ltd
• Subjects: Accuracy; Algorithms; Classification; cluster-wise anisotropic data; Clustering; Datasets; Entropy; Experiments; fuzzy clustering; Informatics; Probability distribution; Regularization; t-distribution; Tsallis entropy-regularization

This study proposes a fuzzy clustering algorithm based on fuzzy classification maximum likelihood, t-distribution, and Tsallis entropy regularization. The proposed algorithm is shown to be a generalization of the two conventional algorithms, not only in the use of their objective functions, but also...