关键词: 变精度粗糙集模型, 决策树, 误差参数, 加权分类粗糙度

Abstract:

Aiming at the problems of complex and low accuracy decision tree constructed by ID3, a new decision tree classification algorithm based on the Variable Precision Rough Set Model is proposed in this article, which takes the weighted classification rough degree as the heuristic function of choosing attributes at a node, this heuristic function can more synthetically measure the contribution of an attribute for classification,and is simpler in calculation than information gain too, which can eliminate the effect of noise data on choosing attributes and generating leaf nodes.Experiments prove that the size of trees generated by the new algorithm is superior to the ID3 algorithm.

Key words: variable precision rough set model;decision tree;error parameter;weighted