Data Classification Based on the Class-Rooted FP-Tree Approach
Ye‐In Chang, Chen Wu, Jun-Hong Shen, Chien‐Hung Chen · 2009
In this paper, we present an efficient and accurate decision tree building method which resolves some problems and reduces the overhead of database scanning in the CAM method. We also build a structure named class-rooted FP-tree. From our simulation, we show that the performance of the proposed class-rooted FP-tree mining method is better than the CAM methods in terms of storage usage, the times of database scanning and classification accuracy.