基于距离的K-Means划分式聚类算法及其编程实现

Application of K-Means partition type clustering algorithm based on distance

K-Means算法是划分式聚类算法。本文通过在应用中的编程实现分析了基于欧式距离的划分式聚类算法的基本原理、实现步骤和编程时的注意事项,最后分析了该算法的优缺点。

K-Means is clustering algorithm of partition type. This paper is about this algorithm based on Euclidean distance and through the in application programming explains the funda- mental, approaches and notes when program. In the end analysis the advantage and disadvan- tage of this algorithm.