文件名称:MultivariateDecisionTree-
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单变量的决策树算法造成树的规模庞大,规则复杂,不易理解。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。
-Decision Tree Algorithm in univariate tests caused large-scale, complex rules that are difficult to understand.
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
度的方法,提出了一种新的多变量决策树算法。
-Decision Tree Algorithm in univariate tests caused large-scale, complex rules that are difficult to understand.
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
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一种多变量决策树的构造与研究_陈广花.caj
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