An effective clustering scheme for high-dimensional data

• Published in: Multimedia tools and applications Vol. 83; no. 15; pp. 45001 - 45045
• Main Authors: He, Xuansen, He, Fan, Fan, Yueping, Jiang, Lingmin, Liu, Runzong, Maalla, Allam
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.05.2024; Springer Nature B.V
• Subjects: Algorithms; Cluster analysis; Clustering; Computer Communication Networks; Computer Science; Data Structures and Information Theory; Datasets; Discriminant analysis; Empirical analysis; Multimedia Information Systems; Normal distribution; Special Purpose and Application-Based Systems; Linear discriminant analysis; Silhouette analysis; Clustering validity function; Initial center selection; Empirical rule; means algorithm

While the classical K -means algorithm has been widely used in many fields, it still has some defects. Therefore, this paper proposes a scheme to improve the clustering quality of K -means algorithm. The farthest initial center selection and the min–max rule are used to improve the random initializa...