聚类分析中CLARA算法的分析与实现

Analysis and implementation of CLARA algorithm on clustering

讨论了CLARA算法的基本思想,给出了CLARA算法的步骤,并分析其计算复杂性.然后以MapInfo为平台,用MapBasic编程,将算法分为样本数据抽取、聚类划分、代价计算3部分,对CLARA算法的设计与实现进行了系统的分析.

We first discuss the basic thought, give the step of CLARA algorithm in succession, and analyze the computing complexity. Then we code by MapBasic on the Mapinfo flat roof, discuss designing and implementation of CLARA algorithm through partitioning the algorithm into three parts, sample data sets extracting, cluster partition and cost computing.