Cross-Validating and Bagging Partitioning Algorithms with Variable Importance
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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.
Subject Area:
Statistical Models, Statistical Theory and Methods
Suggested Citation:
Annette M. Molinaro and Mark J. van der Laan, "Cross-Validating and Bagging Partitioning Algorithms with Variable Importance" (August 2005). U.C. Berkeley Division of Biostatistics Working Paper Series. Working Paper 185.
http://www.bepress.com/ucbbiostat/paper185