Cross-Validating and Bagging Partitioning Algorithms with Variable Importance

Annette M. Molinaro, Division of Biostatistics, Yale University School of Medicine
Mark J. van der Laan, Division of Biostatistics, School of Public Health, University of California, Berkeley

Abstract

We present a cross-validated bagging scheme in the context of partitioning algorithms. To explore the benefits of the various bagging scheme, we compare via simulations the predictive ability of single Classification and Regression (CART) Tree with several previously suggested bagging schemes and with our proposed approach. Additionally, a variable importance measure is explained and illustrated.