A Outlier Mining Algorithm Based on Principal Component Analysis
一种基于主成分分析的异常点挖掘方法

Based on the analysis of the existing algorithms of outlier mining,a new outlier mining algorithm is put for- ward based on principal component analysis,it clustering firstly with Density-based algorithm,and determine outliers according to principal component analysis within the sparse samples around the clusters that it don't contain any clus- ters,experimental results show the feasibility and effectiveness of the new algorithm.