The Research on Clustering Ensembles Selection Algorithm based on Semi-supervised K-means Clustering. Issue 1 (January 2021) - Wu, Xiaoxuan; Guo, Changjian; Hu, Tanglei
Abstract: Selective clustering ensemble algorithm can eliminate the inferior quality clustering member's influence and can achieve a better clustering solution relative to the clustering ensemble algorithm. For high dimensional data clustering, in this paper, a novel selective ensemble algorithm based on semi-supervised K-means clustering is proposed. In this paper, through a large number of experiments to verify the validity of the proposed algorithm for dealing with high dimensional data clustering. The new algorithm can achieve statistically significant performance improvement over other clustering algorithms.