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中文摘要：
在容差关系下，针对属性集P在分类中的不同个体贡献，引入粗糙集的近似度概念，结合属于，不属于集合％㈨的元素贡献的不确定性，定义一种新的知识熵，从而实现基于近似度的不完备信息系统属性约简算法。仿真结果表明，与IEARA算法相比，该算法具有较高的约简效率。
英文摘要：
This paper considers the differences of the individual contribution based on attribute set P classification in the tolerance relation, introduces the notion of approximate degree for the rough set. It defines a new entropy based on the consideration of both the elements belong to a set of Rp（x） and does not belong to Rp（x）. On this basis, an attribute reduction algorithm based on approximate degree for incomplete information system is realized. Simulation results show that this algorithm has better reduction efficiency than IEARA algorithm.
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