This paper introduces a novel model selection procedure for tree-based classifiers. The method is based on the bootstrap 632+ rule recently proposed by Efron and Tibishirani. The rule allows to select compact, non-overfitting classification trees by reweighting the contributions of the resubstitution and standard bootstrap estimated errors. The proposed method is applied in a medical entomology problem for modeling the risk of parasite presence
Selection of Tree-Based Classifiers with the Bootstrap 632+ Rule
Merler, Stefano;Furlanello, Cesare
1997-01-01
Abstract
This paper introduces a novel model selection procedure for tree-based classifiers. The method is based on the bootstrap 632+ rule recently proposed by Efron and Tibishirani. The rule allows to select compact, non-overfitting classification trees by reweighting the contributions of the resubstitution and standard bootstrap estimated errors. The proposed method is applied in a medical entomology problem for modeling the risk of parasite presenceFile in questo prodotto:
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