The Discovery of Attribute Feature Cluster for Any Clustering Result Based on Outlier Detection Technique

The comprehension of the clustering result is a problem that hasn't yet resolve, which having important meaning to the usage of the cluster result and the evaluation of the cluster effect. We put forward the method discovering attribute feature cluster for any clustering result based on outlier detection technique, and put forward an outlier detection algorithm based on even distribution pattern. Through carrying on outlier analysis to all data cluster attribute descriptions, we discovered the feature attribute of each data cluster, and then carried out the comprehension to the clustering result. The remarkable point lies in the method doesn't only aim at a particular clustering algorithm, but also the analysis of any the clustering algorithm result. Experiment to the UCI data set indicated, the method submitted in this paper obtained better result.