On the Behavior of Splitting Criteria for Classification Trees
In the framework of classification trees, the behavior of splitting criteria is investigated through a simulation study and applications on a real data set. Some enphasis is appointed to the strength of the dependency among variables, the choice of the splitting rule, the role played by the type of predictors, the stability of the classification rule. Alternative splitting criteria and new splitting rules are also proposed to deal with the computational effort of splitting procedures in large data sets.
KeywordsClassification Tree Terminal Node Gini Index Classification Rule Misclassification Rate
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