Based on the rough sets theory of attributes reduction,the core of condition attributions and the weighted roughness of condition attributions,a new multivariate decision tree algorithm is proposed.
本文结合粗糙集原理中的相对核及加权粗糙度的方法,提出了一种新的多变量决策树算法。
参考来源 - 一种多变量决策树方法研究·2,447,543篇论文数据，部分数据来源于NoteExpress
According to the value of weighted mean roughness the priority of different characteristic information can be distinguished, so the proposed method possesses strong tolerant ability.
按加权平均粗糙集的大小区分层内各特征信息的优先级，具有很强的容错能力。
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.
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。
We presented weighted mean roughness, a new concept based on rough sets theory which is regarded as the criteria for choosing attributes.
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。
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