一种实域粗糙集模型及属性约简方法

An approach for real domain rough sets model and attribute reduction

通过对实域区间和决策值的重新划分,对已经存在的属性广义重要度度量准则进行了扩展,构建了对象空间上的广义邻域关系及广义邻域关系下的实域粗糙集模型,并在此基础上提出了实域决策系统中属性约简方法(ARRDDS).对不同数据集的实验测试结果表明,与其他相关方法相比,ARRDDS方法能够较好地处理决策表中实数域属性约简问题.

Through repartition for the real domain interval values and the decision classifications, an extended method of calculating the general important degree of an attribute and attribute subsets is proposed. A general neighborhood relation is established on objects space. Then a rough set model is constructed based on the general neighborhood relation. Furthermore, an approach for attribute reduction in a real domain decision system（ARRDDS） is developed. Results of experimental evaluation on different data sets show that ARRDDS has the better performance comparing with the related rough sets approaches of attribute reduction in processing decision tables with real-valued attributes.