聚类算法初始聚类中心的优化

对近年来k-means算法的研究现状与进展进行总结.首先对较有代表性的初始聚类中心改进的算法,从思想、关键技术和优缺点等方面进行分析.其次选用知名数据集对典型算法进行测试,主要从就同一个数据集不同改进算法的聚类情况进行对比分析,为聚类分析和数据挖掘等研究提供有益的参考.

The optimization of original clustering center based on the clustering algorithm

The classic algorithm of k-means is discussed,that is one of the most widespread methods in clustering.But it is sensitive to the original clustering center.The research actuality and new progress in k-means clustering algorithm in recent years are summarized.First,the analysis and induction of some representative improved k-means algorithms of several aspects,such as the ideas of algorithm,key technology,advantage and disadvantage.Second,several typical k-means algorithms and known data sets are selected,experiments are implemented and compared with the same clustering of the data set for the different algorithms.The above work can give a valuable reference for data clustering and data mining.