A new approach based on a rough set and a decision tree to bank customer credit evaluation

摘要

This paper proposes a new approach to Customer Credit Evaluation by synthesizing the Rough Set Theory and Decision Tree Theory. It adopts and improves a algorithm [2] while applying the rough set theory in attribute reduction. It also applies the C4.5 Algorithm proposed by Quinlan to build a decision tree model and adjusts relevant parameters during tree pruning period. Experimental results show that the approach has a better performance in terms of efficiency as well as prediction accuracy.