文章基本信息

标题：Automatic PAM Clustering Algorithm for Outlier Detection
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作者：Lei, Dajiang ; Zhu, Qingsheng ; Chen, Jun 等
期刊名称：Journal of Software
印刷版ISSN：1796-217X
出版年度：2012
卷号：7
期号：5
页码：1045-1051
DOI：10.4304/jsw.7.5.1045-1051
语种：English
出版社：Academy Publisher
摘要：In this paper, we propose an automatic PAM (Partition Around Medoids) clustering algorithm for outlier detection. The proposed methodology comprises two phases, clustering and finding outlying score. During clustering phase we automatically determine the number of clusters by combining PAM clustering algorithm and a specific cluster validation metric, which is vital to find a clustering solution that best fits the given data set, especially for PAM clustering algorithm. During finding outlier scores phase we decide outlying score of data instance corresponding to the cluster structure. Experiments on different datasets show that the proposed algorithm has higher detection rate go with lower false alarm rate comparing with the state of art outlier detection techniques, and it can be an effective solution for detecting outliers.
关键词：outlier detection;PAM clustering algorithm;subtractive clustering;cluster validation