Selection of Tree‐Biased Classifiers with the Bootstrap 632+ Rule
Stefano Merler, Cesare Furlanello · Biometrical Journal · 1997
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 Tibshirani. The rule allows selecting compact, non‐overfitting classification trees by weighting the contributions of the resubstitution and standard bootstrap estimated error. The proposed method is applied in a medical entomology problem for modeling the risk of parasite presence.