Outlier detection is an important field of data mining, which is widely used in credit card fraud detection, network intrusion detection ,etc. A kind of high dimensional data similarity metric function and the concept of class density are given in the paper, basing on the combination of hierarchical clustering and similarity, as well as outlier detection algorithm about similarity measurement is presented after the redefinition of high dimension density outliers is put. The algorithm has some value for outliers detection of high dimensional data set in view of experimental result.
Research on Similarity Measurement Algorithm of High-dimensional Data
