A New Decision Tree Construction Using the Cloud Transform and Rough Sets
Many present methods for dealing with the continuous data and missing values in information systems for constructing decision tree do not perform well in practical applications.In this paper,a new algorithm,Decision Tree Construction based on the Cloud Transform and Rough Set Theory under Characteristic Relation (DTCCRSCR),is proposed for mining classification knowledge from the data set.The cloud transform is applied to discretize continuous data and the attribute whose weighted mean roughness under the characteristic relation is the smallest will be selected as the current splitting node.Experimental results show the decision trees constructed by DTCCRSCR tend to have a simpler structure,much higher classification accuracy and more understandable rules than C5.0 in most cases.
Rough sets Cloud transform Decision trees Weighted mean roughness Characteristic relation
Jing Song Tianrui Li Da Ruan
School of Information Science and Technology Southwest Jiaotong University,Chengdu 610031,P.R.China; School of Information Science and Technology Southwest Jiaotong University,Chengdu 610031,P.R.China Belgian Nuclear Research Centre SCK·CEN,2400 Mol,Belgium Transportation Research Institute,Hasselt U
国际会议
成都
英文
524-531
2008-05-17（万方平台首次上网日期，不代表论文的发表时间）