CC4.5: Cost-sensitive Decision Tree Pruning
Jianghui Cai, John R. Durkin, Qianfeng Cai · WIT transactions on information and communication technologies · 2005
There are many methods to prune decision trees, but the idea of cost-sensitive pruning has received much less investigation even though additional flexibility and increased performance can be obtained from this method. In this paper, we introduce a cost-sensitive decision tree pruning algorithm called CC4.5 based on the C4.5 algorithm. This algorithm uses the same method as C4.5 to construct the original decision tree, but the pruning methods in CC4.5 are different from that in C4.5. CC4.5 includes three cost-sensitive pruning methods to deal with misclassification cost in the decision tree. Unlike many other pruning algorithms, CC4.5 uses intelligent inexact classification to consider both error and cost when pruning. Moreover, experiments show that CC4.5 results in improved decision trees with respect to the cost and its comprehensibility and accuracy are also satisfactory.