基于k-means聚类算法的研究

Firstly, the paper analyzes and research the method of cluster analysis, analyzes and compares many kinds of algorithms of cluster analysis, discusses their respective strengths and weaknesses. At the same time, according to the weaknesses of the cluster result of original k-means algorithm is significant influence by selecting the initial cluster centers randomly, a modified algorithm is proposed. Through taking sample many times to data set, choose final superior cluster center, bring down the impact of initial cluster centers to improved algorithm greatly.Simultaneously, the initial data is standadized once the initial cluster center is selected, makes cluster effect improved furthermore. Detecting new algorithm Hk-means through the date of UCI data set, the result shows that Hk-means algorithm is more prominent improved than initial k-means algorithm in cluster effect, and it's useful for conference to relative field.