关键词: 自组织特征映射, 大规模应用聚类, 聚类, 替换代价

Abstract: The basic idea of Self-Organizing Feature Maps（SOFM） algorithm and Clustering LARge Applications（CLARA） algorithm is introduced.Firstly this paper adopts the SOFM algorithm clustering on the data set to attain the class number and the neurons’s connection weights vector，and then the clustering result is used to initialize the class number and the k medoid in the CLARA algorithm.The simulate experiment shows that this clustering method can improve the clustering performance.

Key words: Self-Organizing Feature Maps（SOFM）, Clustering LARge Applications（CLARA）, clustering, replace cost