摘要
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。
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.
出处
《计算机应用》
CSCD
北大核心
2005年第8期1853-1855,共3页
journal of Computer Applications
关键词
粗糙集
数据挖掘
决策树
值约简
分类规则
<Keyword>rough set
data mining
decision tree
value reduction
classing rule