A Novel K-Means Clustering Algorithm and Its Application

Abstract

K -Means algorithm has been researched adequately in recent years. Clustering result of traditional K -Means algorithm is affected by the choice of initial point and noise. In addition to, traditional K -Means algorithm only favors clusters with spherical shapes and similar sizes. A novel K -Means algorithm combining K -Means algorithm and KNN algorithm called KK -Means is proposed to solve these weaknesses in this paper. Experimental result shows that KK -Means algorithm has better performance more than traditional K -Means algorithm.