An outlier detection algorithm based on clustering ensemble

An outlier mining algorithm based on the clustering ensemble was presented in order to reduce the reliance for users and decrease the high false positive rate due to taking the small size clusters as the outliers directly.Outliers can be found according to the abnormal frequency of every record.The algorithm is able to provide the user a more friendly operation.The experimental results on the real-life datasets showed that the proposed algorithms are feasible and effective comparing with other classical algorithms and can be used for mixed dataset.