Huddle based Harmonic K means Clustering Algorithm

Abstract

Clustering method is one of the important methods in data mining. This method will weight the clustering result directly. This paper discusses, the traditional k-means clustering algorithm, analyzing its shortcomings clustering algorithm and measuring the harmonic based distance between each data object and cluster centers. This efficient method avoids the need to compute the distance of each data object to the cluster center. It saves the running time. The experimental results show that this efficient method can effectively improve the speed of clustering and accuracy, reducing the computational time.

Keywords: Data Mining; Clustering analysis; k means algorithm