在构造决策树的过程中，分离属性选择的标准直接影响分类的效果。

In the process of constructing a decision tree, the criteria of selecting partitional attributes will influence the efficiency of classification.

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基于粗糙集的理论提出了加权平均粗糙度的概念，将其作为选择分离属性的标准。

We presented weighted mean roughness, a new concept based on rough sets theory which is regarded as the criteria for choosing attributes.

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然后采用加权平均粗糙度的概念，作为选择分离属性的标准，构造电网故障决策树，从而实现对电网的故障诊断。

Then the decision tree of electric power grid diagnosis is built by using weighted mean roughness as separating attributes standard to realize electric power grid fault diagnosis.

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