计算机科学 ›› 2016, Vol. 43 ›› Issue (Z6): 40-43.doi: 10.11896/j.issn.1002-137X.2016.6A.008
徐菲菲,毕忠勤,雷景生
XU Fei-fei, BI Zhong-qin and LEI Jing-sheng
摘要： 经典粗糙集属性约简基本都是保持正域、负域和边界域不变,而决策粗糙集对属性的增减过程不具备单调性,因此不可能同时保持3个区域均不变。在决策粗糙集模型中,作出决策更应该考虑风险最小化原则,因此提出一种改进的风险最小化属性约简方法,在属性的选取过程中同时考虑所选取的属性子集对决策的划分能力,即联合属性重要度以及风险最小化。实验证明所提方法是有效的。
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