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- W2367250285 abstract "Decision tree pruning can improve the prediction accuracy of decision tree. Cost-Complexity Pruning( CCP)and other commonly used pruning algorithms take reducing misclassification rate as the pruning basis. Akaike Information Criterion( AIC) can be used as criterion to assess decision tree. A new decision tree pruning algorithm based on AIC was proposed, and the comprehensive evaluation of the probability of correct classification rate and the complexity of decision tree was used as the pruning basis. In the applied example, the pruning algorithm based on AIC made the decision tree classify more accurately without overfitting and insufficient pruning." @default.
- W2367250285 created "2016-06-24" @default.
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- W2367250285 date "2014-01-01" @default.
- W2367250285 modified "2023-09-22" @default.
- W2367250285 title "Pruning algorithm of classificaiton and regression decision tree based on Akaike information criteria" @default.
- W2367250285 hasPublicationYear "2014" @default.
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