基于粗糙集和SAT的属性约简

Attribute Reduction Based on Rough Sets and Propositional Satisfiability

属性约简是数据挖掘中的一种粗糙集方法,它决定了能代表整个信息系统的重要属性的集合。本文提出了一种求最小约简的基于命题可满足性(简称SAT)的算法,提出一个解决SAT问题的分割和结合的算法。实验结果表明,本文所提算法在高准确分类的基础上,在所得约简中大大减少了规则的数目。

Attribute reduction is a rough set approach in data mining that determines the set of important attributes to represent the IS.An algorithm in finding minimal reduction based on Propositional Satisfiability(abbreviated as SAT) algorithm is proposed.A branch and bound algorithm is presented to solve the proposed SAT problem.The experimental result shows that the proposed algorithm has significantly reduced the number of rules generated from the obtained reduction with high percentage of classification accura...