计算机应用与软件2011，Vol.28Issue(11)：119-121,124,4.
基于类轮廓层次聚类方法的研究
RESEARCH ON CLASS-PROFILE-BASED HIERARCHICAL CLUSTERING METHOD
摘要
Abstract
Traditional clustering algorithms are often incapable of roundly considering the connectivity and similarity characteristics among classes. The thesis firstly presents the fundamental definition of class boundary point and class profile; secondly, with comprehensive consideration based on connectivity characteristics and similarity characteristics among classes, defines some standards and methods for inter class similarity measurement; thirdly, proposes a class-profile-based hierarchical clustering algorithm, which is able to effectively process arbitrary shaped clusters and distinguish isolated points from noise data. The feasibility and effectiveness of the algorithm is validated through clustering analysis on image data sets and Iris standard data sets.关键词
连通性/近似性/类轮廓/层次聚类Key words
Connectivity Proximity Class profile Hierarchical clustering分类
信息技术与安全科学引用本文复制引用
孟海东,唐旋..基于类轮廓层次聚类方法的研究[J].计算机应用与软件,2011,28(11):119-121,124,4.基金项目
国家自然科学基金资助项目(40762003) （40762003）
教育部"春晖计划"合作研究项目(Z2009-1-01041) （Z2009-1-01041）
