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为了准确度量属性的重要性,从基于粗糙集的属性度量视角,提出一种基于混合度量机制的属性评价方法,该方法从不同的信息粒度分析属性的重要性.在混合度量机制中,根据数据分布特点引入参数权重因子.在此基础上,构造一种基于粗糙集属性度量机制的集成分类器.通过实验结果和比较分析表明,所提出的方法能有效地降低数据的属性维度,相比较于单一属性度量准则,分类器具有更好的分类性能.
In order to accurately measure the importance of attributes, an attribute evaluation method based on hybrid metrics is proposed from the perspective of attribute metrics based on rough sets, which analyzes the importance of attributes from different information granularities.In mixed metrics, This paper proposes an integrated classifier based on the attribute metric of rough set.Experimental results and comparative analysis show that the proposed method can effectively reduce the attribute dimension of data, The single attribute measure criterion, the classifier has the better classification performance.