A Novel Data Purification Algorithm Based on Outlier Mining

Abstract

This paper presents a data purification algorithm based on outlier mining. In order to implement the purifying of training data, we define the central bias function of complex events and dissimilarity function of event set, and put forward an exception set growth algorithm based on bias priority. Experiment proves that the algorithm can solve non-deterministic polynomial hard and control the algorithm complexity within polynomial complexity.