Alternative Evaluation Criterion of Constructing Decision Tree of Discrimination
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摘要: 讨论了一种新的判别决策树评价准则,在建立二分树的过程中,提出采用不可分辨度最大下降作为选择自变量的原则.这种新准则与经典的非纯度下降算法在概念上是近似的.如果适当定义非纯度下降算法中的权重,则这两个准则就是完全等价的.然而,新准则的计算更加简单,并且通过案例分析可知,对新准则计算结果的解释也更加容易.Abstract: An alternative criterion of evaluating the built decision tree for discrimination is discussed in this paper. The maximal decrease in undistinguished degree is proposed as the principle to choice explanatory variable for building a binary tree. From the basic concept, this new criterion is approximately consistent with the classical method using decrease in impurity. Though these two criteria are equivalent if choosing appropriate weights for the classical algorithm of decrease in impurity. The research shows that the computation of new criterion is more simple. Moreover, the result from the case study shows that the new criterion is more interpretable.
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Key words:
- discriminant analysis /
- decision trees /
- purity /
- undistinguished degree
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[1] Lebart L, Morineau A, Piron M. Statistique exploratoire multidimensionnelle . Paris:DUNOD,1995. [2]Celeux G. Analyse discriminante sur variables continues[M]. Paris:INRIA, 1990. [3]刘永才,张 卫. 布尔方法理论[M].上海:上海科学技术文献出版社, 1993.
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