关键词: 孤立点检测, 层次聚类, 数据预处理, 数据挖掘

Abstract: Outlier detection is an important step of data mining，a new Outlier Detection method based on Hierarchical Clustering（ODHC） is proposed.ODHC method takes an analysis based on the results of hierarchical clustering，and detects outliers by the distance matrix in decending order of distance between clusters.Outlier in the specified degree of isolation can be detected，until it meets the user’s requirement of data-intensive.This method is applicable to multi-dimensional data sets，and the algorithm is principle-intuitive，user-friendly，and high accuracy in outlier detection.Experimental results on iris and balloon data sets show that ODHC method can effectively identify the outliers，and is a simple and applicable method of outliers detection.

Key words: outlier detection, hierarchical clustering, data preprocessing, data mining