Data Mining Based on Rough Set and Decision Tree Optimization
In this paper, the authors present a new kind of decision tree classification algorithm based on rough set theory. The growth of decision tree and tree pruning algorithms are analyzed and compared. And optimizes the decision tree algorithm from two aspects: attribute reduction and pruning. They present a reduction algorithm which is called ER briefly, based on the attribute dependency and a pruning algorithm for decision tree based on rough set theory. The proposed algorithm which is used in the supplier evaluation system verifies the validity by comparing with C4.5 algorithm.