Classification with Tree-Based Ensembles Applied to the WCCI 2006 Performance Prediction Challenge Datasets
Corinne Dahinden · The 2006 IEEE International Joint Conference on Neural Network Proceedings · 2006
Our contribution to the WCCI 2006 Performance Prediction Challenge is built on a modified Random Forests scheme, with cross-validation as a means for tuning parameters and estimating error-rates. This simple and computationally very efficient approach was found to yield better predictive performance than many algorithms of much higher complexity.