基于粗糙理论的属性约简在决策树中的应用

Application of Property Reduction in Decision Tree Based on Rough Theory

分类问题是数据挖掘和机器学习中的一个核心问题。为了得到最高的分类准确率,决策树分类过程中,决策属性的选择非常关键。分析了粗糙理论的属性约简方法,提出了基于粗糙理论的属性约简在决策树中的应用,并产生多个相对约简的选择问题。

Classification is a core problem in data mining and machinery learning. In order to obtain the maximum classification precision, it is so important to select the proper decision tree in the process of classification of decision tree.This paper analyzes the method of property reduction about rough theory and applies it to decision tree, which can produce multiple choice problems of relative reduction.