Local peculiarity oriented data mining and its application in outlier detection
作者： JIAN YANG , NING ZHONG , YIYU YAO , JUE WANG
DOI: 10.1142/S0219622012500319
关键词:
摘要: Peculiarity oriented mining (POM), aimed at discovering peculiarity rules hidden in a dataset, is data method. factor (PF) one of the most important concepts POM. In this paper, it proved that PF can accurately characterize sampled from normal distribution. However, for general one-dimensional distribution, does not have property. A local version PF, called LPF, proposed to solve difficulty. LPF effectively describe continuous Based on framework presented, which consists two steps, namely, peculiar identification and analysis. Two algorithms case study analysis are given make practical. Experiments several benchmark datasets show their good performance.
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