基于值约简和决策树的最简规则提取算法

粗糙集理论中的值约简和数据挖掘领域中的决策树都是有效的分类方法,但二者都有其局限性。将这两种方法结合起来,生成一种新的基于值核的极小化方法对决策树进行修剪,提出了约简规则的判定准则,缩小了约简的范围,最后再对生成的规则进行极大化处理,以保证规则覆盖信息的一致性,实验验证了该算法的有效性。

Algorithm based on value reduction and decision tree to generate minimal rules

Value reduction in rough set theory and decision tree in data mining are effectively used in the classification, but each of them has shortcomings. Those two methods were combined to generate a new minimal method based on value core to pollard the decision tree. Then judgmental standards of rule reduction were proposed to decrease the quantity of reducted rules. In the end, the classing rules were dealed with by maximal method to ensure the consistency of the knowledge contained by the rules. The algorithm is efficient which was proved by the experiment.