计算机技术与发展2011，Vol.21Issue(3)：76-78,3.
一种基于引力的分层聚类算法
A Hierarchical Clustering Algorithm Based on Gravity
摘要
Abstract
Thc traditional hierarchical clustering algorithm for clustering process, only uses the distance between samples as the sole criterion for similarity, this description is too simple. Associated with the formation of galaxies in the universe is essentially a clustering process by gravitational attraction between galaxies role. Introduce the idea of hierarchical gravitational clustering, propose a hierarchical clustering algorithm based on gravitational HCBG ( Hierarchical Clustering Base Gravity), from two aspects of the distance between the samples and the cluster size classes more accurately depicts the similarity. The hierarchical clustering process is regarded as the sample points based on "gravity" to attract spontaneous process. Use UCI machine learning datahase: Iris, Wine nnd Glass as data sets, experimental results show that the proposed algorithm HCBG clustering results than classical hierarchical clustering based on distance HC ( Hierarchical Clustering) increase 5％ ～ 10％ or so.关键词
引力/分层聚类/相似度分类
信息技术与安全科学引用本文复制引用
贾瑞玉,查丰,耿锦威,宁再早..一种基于引力的分层聚类算法[J].计算机技术与发展,2011,21(3):76-78,3.基金项目
安徽省自然科学基金项目(KJ2008B092) （KJ2008B092）
