A Novel Data Purification Algorithm Based On Outlier Mining

摘要：

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 nondeterministic polynomial hard and control the algorithm complexity within polynomial complexity.

关键词： data mining outlier data purification exception set

作者: Jianfeng Dong Xiaofeng Wang Feng Hu Liyan Xiao

作者单位: School of Information Management, Wuhan Uinversity, Wuhan, China School of Computer Science, Huazhong University of Science & Technology, Wuhan, China College of Foreign Language, Jishou University, Zhang Jiajie, China

会议类型: 国际会议

会议名称: 2009 Ninth International Conference on Hybrid Intelligent Systems(第九届混合智能系统国际会议 HIS 2009)

会议地点: 沈阳

会议语种:英文

页码: 1-4

在线出版日期: 2009-08-12（万方平台首次上网日期，不代表论文的发表时间）