自行implement的k-mean(含fuzzy c mean),可以直接於vc++針對大量數據 M行分群的動作()

克服K均值聚类算法易受初始聚类中心影响的缺点，优化K均值聚类算法(The K mean clustering algorithm is easily affected by the initial cluster center, and the K mean clustering algorithm is optimized.)

使用R语言进行聚类分析的例子，包括层次聚类，k均值聚类，密度聚类等(Examples of clustering analysis using R language, including hierarchical clustering, K mean clustering, density clustering, etc.)