关键词: K-means算法, 聚类, 初始聚类中心, TDKM算法

Abstract: To solve this problems that the traditional K-means algorithm has sensitivity to the initial cluster centers, a new improved K-means algorithm is proposed. The algorithm builds minimum spanning tree and then splits it to get K initial clusters and the relevant initial cluster centers. The initial cluster centers are found to be very closed to the desired cluster centers for iterative clustering algorithms. Theory analysis and experimental results demonstrate that the improved algorithms can enhance the clustering performance, get stable clustering in a higher accuracy.

Key words: K-means algorithm, clustering, initial clustering centers, TDKM algorithm