文章基本信息

标题：The Unification and Assessment of Multi-Objective Clustering Results of Categorical Datasets with H-Confidence Metric
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作者：Onur C. Sert (TOBB Economics ; Technology University ; Turkey) Kayhan Dursun (TOBB Economics 等
期刊名称：Journal of Universal Computer Science
印刷版ISSN：0948-6968
出版年度：2012
卷号：18
期号：4
出版社：Graz University of Technology and Know-Center
摘要：Multi objective clustering is one focused area of multi objective optimization. Multi objective optimization attracted many researchers in several areas over a decade. Utilizing multi objective clustering mainly considers multiple objectives simultaneously and results with several natural clustering solutions. Obtained result set suggests different point of views for solving the clustering problem. This paper assumes all potential solutions belong to different experts and in overall; ensemble of solutions finally has been utilized for finding the final natural clustering. We have tested on categorical datasets and compared them against single objective clustering result in terms of purity and distance measure of k-modes clustering. Our clustering results have been assessed to find the most natural clustering. Our results get hold of existing classes decided by human experts.
关键词：NSGA-II, h-confidence, multi-objective clustering