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A Heuristic Algorithm for Selective Calculation of a Better Relative Reduct in Rough Set Theory

机译:粗糙集理论中相对较好约简选择性计算的启发式算法

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摘要

In this paper, we consider a heuristic method to partially calculate relative reducts with better evaluation by the evaluation criterion proposed by the authors. By using the average of certainty and coverage of decision rules constructed from each condition attribute, we introduce an evaluation criterion of condition attributes, and consider a heuristic method for calculating a relative reduct with better evaluation.
机译:在本文中,我们考虑了一种启发式方法,可以根据作者提出的评估标准更好地评估部分折减率。通过使用确定性的平均值和从每个条件属性构造的决策规则的覆盖范围,我们引入了条件属性的评估标准,并考虑了一种启发式方法来计算具有更好评估的相对约简。

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