Improved CBA classification algorithm based on rough set
Zheng Tan, Hanhu Wang, Mei Chen, Xiao-Ping Steven Zhang · 2009
CBA is a classification algorithm integrating association rule mining and classification. CBA has been widely used in data mining areas because it has higher accuracy than C4.5. When the samples become more and more large and characteristic attributes become more and more numerous, CBA algorithm becomes much lower. In this paper, an improved CBA algorithm based on rough set is proposed. The improved CBA algorithm applies rough set to induce attributes, and prune candidate rules with PEP method. Experimental results illustrate that the improved CBA algorithm is efficient and it has higher accuracy than CBA and C4.5.