00000cab a22000003a 4500 UP-99796217609532914 Buklod 20231007234344.0 m |o d | ta 101110s xx d | ||r ||||| || DENGII eng Krishnapuram, R. Clustering algorithms based on volume criteria. pp. 228-236 Clustering algorithms such as the K-means algorithm and the fuzzy C-means algorithm are based on the minimization of the trace of the (fuzzy) within-fluster scatter matrix. In this paper, we explore the use of determinant (volume) criteria for clustering. We derive an algorithm called the minimum scatter volume (MSV) algorithm, that minimizes the scatter volume, and another algorithm called the minimum cluster volume (MCV) that minimizes the sum of the volumes of the individual clusters. The behavior of MSV is shown to be similar to that of K-means, whereas MCV is more versatile K-means algorithm. MCV algorithm. MSV algorithm. Clustering. Clustering algorithms. Determinant criteria. Fuzzy C-means algorithm. Fuzzy within-fluster scatter matrix. Minimum cluster volume algorithm. Minimum scatter volume algorithm. Trace minimization. Volume criteria. IEEE Transactions on fuzzy systems 8, 2 (2000). FO UPD DENG-II Article