【摘要】 属性约简是粗糙集理论的核心问题之一,也是粗糙集有效算法研究的焦点。为获得最简明的规则集,通常希望能找出最小的属性约简集,但得到最优解NP-hard的问题,通常采取启发式的算法得到近似最优解。文中研究了不完全决策表的属性约简,提出了对不完全决策表的一种基于信息熵的属性约简算法,并通过例子说明算法的具体过程和验证了算法的可行性。对寻找对象的相似类的步骤则在排序和二分查找的基础上提出了一种高效的算法,这样就相应地提高了属性约简算法的效率。更多还原

【Abstract】 The attribute reduction is a core problem of the rough set theory,also is the focal point of algorithm research for rough set.In order to get the most simple rule set,people wish to get the smallest attribute reduction set.the attribute reduction algorithm based on information entropy for an incomplete decision table is introduced in the paper. An example is given in the paper to illustrate the steps of the algorithm and to test the feasibility of the algorithm. An efficient algorithm to seek the set of objects similar to the considered object based on sort and binary search is also advanced in the paper and the efficiency of the attribute reduction algorithm is improved accordingly.更多还原