A Comparison of Six Approaches to Discretization-A Rough Set Perspective

摘要：

We present results of extensive experiments performed on nine data sets with numerical attributes using six promising discretization methods.For every method and every data set 30 experiments of ten-fold cross validation were conducted and then means and sample standard deviations were computed.Our results show that for a specific data set it is essential to choose an appropriate discretization method since performance of discretization methods differ significantly.However,in general,among all of these discretization methods there is no statistically significant worst or best method.Thus,in practice,for a given data set the best discretization method should be selected individually.

关键词： Rough sets Discretization Cluster analysis Merging intervals Ten-fold cross validation Test on the difference between means F-test

作者: Piotr Blajdo Jerzy W.Grzymala-Busse Zdzislaw S.Hippe Maksymilian Knap Teresa Mroczek Lukasz Piatek

作者单位: Department of Expert Systems and Artificial Intelligence,University of Information Technology and Ma Department of Electrical Engineering and Computer Science,University of Kansas,Lawrence,KS 66045,USA Department of Distributed Systems,University of Information Technology and Management,35-225 Rzeszow

会议类型: 国际会议

会议名称: The Third International Conference on Rough Sets and Knowledge Tevhnology(RSKT 2008)(第三届粗糙集与知识技术国际会议)

会议地点: 成都

会议语种:英文

页码: 31-38

在线出版日期: 2008-05-17（万方平台首次上网日期，不代表论文的发表时间）