关键词: 异常检测, 邻域密度, 混合数据

Abstract: This paper proposes a neighborhood density based outlier detection method, which is applicable to the data with mixed numerical and categorical features. In this method, the outlierness indicator of a sample is defined as the weighted sum of neighborhood cardinality and  average neighborhood density of this sample. To validate the effectiveness of this algorithm, it performs a series of experiments. Experimental results show that the proposal is applicable and effective to mixed data.

Key words: outlier detection, neighborhood density, mixed data