A Data Mining Algorithm Based on Improved K-Means Clustering

Abstract

This paper purposes a K-means clustering algorithm based on improved filtering process. Thealgorithm improves the filtering process,The two minimum sample points are reasonable initial clustering centers. It makes the probability summary of data in a cluster as large as possible, and the probability summary of data in different clusters as small as possible. Experimental results show that the proposed algorithm can select the proper initial clustering center, and it is more compact and robust than thetraditional K-means clustering algorithm.