一种快速差别矩阵属性约简算法

Fast attribute reduction algorithm based on discernibility matrices

为了解决基于差别矩阵属性约简的计算效率问题,分析了基于差别矩阵的属性约简算法的不足,给出了新的差别矩阵的定义,大大减少了差别矩阵中非空元素的个数,提高了属性约简算法的效率。利用单个属性的不可辨识性来计算出现频率最多的属性,进一步降低差别矩阵的大小,并设计了基于新的差别矩阵的快速属性约简算法。对UCI一些数据库进行了仿真,实验结果表明了新算法具有高效性。

In order to solve the efficiency problem of calculating the attribute reduction based on discernibility matrices,the shortcomings of attribution reduction algorithm are analyzed based on discernibility matrices,and the definition of the new discernibility matrices is presented.It decreases greatly the number of non-empty elements,which improves the efficiency of algorithm for attribute reduction based on discernibility matrices.And an attribute with indiscernibility can be used to compute the attribute with more frequencies for generating smaller discernibility matrices.A new algorithm based on the improved discernibility matrices is proposed.An example is used to illustrate the efficiency of the new algorithm.The simulation experiments for UCI databases show that the new algorithm is efficient for various kinds of data sets.