基于粗糙集的快速属性约简算法研究

Fast Attribute Reduction Algorithm Based on Rough Sets

通过分析现有相容决策表属性约简算法,找出了计算低效性的根源。新的约简算法从论域的角度出发,采用层次结构,用属性边界域作为度量属性重要性启发函数。该算法使得论域不断缩小的同时,又能选出反映决策表系统特征的重要属性。理论分析和实验表明,该算法保证在分类精度不变的前提下,获得最优或次优的约简属性集。

Through analysing the attribute reduction algorithms of consistent decision table, reasons of inefficiency are found. A new algorithm is proposed which adopts hierarchy structure and boundary of attribute as heuristic function to choose the essential attribute. It can select the important attributes that reflect the characteristic of system while the universal is decreasing. Theoretical analysis and experiment results show that on the premise of unchanged of classification precision, the algorithm can obtain the best or sub-best attribute reduce set.