基于属性关联的约简算法

针对启发式约简算法难以获得最小约简的问题，研究属性之间的排斥与吸引等关联特性，给出属性重要度计算指数。在此基础上，结合属性频率方法，提出基于属性关联的启发式约简算法。该算法以最小约简为目标，采取兼顾单个属性的辨识能力以及属性之间关联的约简策略。实验结果表明，该算法比属性频率方法以及一些同类算法具有更少的属性启发次数，计算结果大部分为最小约简。

Reduction Algorithm Based on Attribute Correlation

To obtain an optimal reduct in heuristic reduction methods, the attraction and repulsion correlations of attributes are analyzed and a definition of attribute significance is presented. On this basis, a heuristic reduction method based on attribute correlation is proposed to calculate an optimal reduct, which integrates the discernibility ability of the single attribute and the correlation among attributes. The experimental results show that the proposed method employs less heuristic calculations than the similar methods and the method based on attribute frequency, and it is more effective to obtain the optimal reduct.