基于有序差别集和属性重要性的属性约简OACSCDCSTPCD
Attribute Reduction Based on Ordered Discernibility Set and Significance of Attribute
针对粗糙集理论的属性约简问题,提出新的差别矩阵简化算法,该算法在无需排序和较少遍历次数的情况下简化了差别矩阵,明显提高了简化速度并最终得到简化的有序差别集.实验验证了该算法的高效性；给出度量属性重要性的新标准,即根据属性所在差别矩阵元素的权重、在差别集中出现的频数和吸收能力3方面采度量其重要性；在上述两者基础上,提出一种基于有序差别集和属性重要性的属性约简新方法,理论分析证明新方法的最坏时间复杂度低于其它基于差别矩阵的属性约简算法.大量实验结果也…查看全部>>
A new improved algorithm for the simplified discernibility-matrix was proposed on the subject of attribute reduction in rough set theory. Discernibility-matrix is being simplified without being sorted and at fewer cost of traversing. This can notably raise the speed of being simplified discernibility-matrix and ultimately obtain the ordered and simplified discernibility set The comparative experiments on computational efficiency show that this new algorithm …查看全部>>
张迎春;王宇新;郭禾
大连理工大学软件学院 大连 116024大连理工大学计算机科学与技术学院 大连 116024大连理工大学软件学院 大连 116024
信息技术与安全科学
粗糙集属性约简简化差别矩阵差别集属性重要性
Rough set, Attribute reduction,Simplified discernibility-atrix.Discernibility set,Significance of attribute
《计算机科学与探索》 2011 (10)
243-247,5
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