1.11. Ensembles: Gradient boosting, random forests, bagging, voting, stacking# Ensemble methods combine the predictions of several base estimators built with a given learning algorithm in order to improve generalizability / robustness over a single estimator. Two very famous examples of ensemble methods are gradient-boosted trees and random forests. More generally, ensemble models can be applied t
1. 1 RecSys ’13, Hong Kong, China, Oct. 12, 2013 Learning to Rank for Recommender Systems Alexandros Karatzogloua , Linas Baltrunasa, Yue Shib aTelefonica Research, Spain bDelft University of Technology, Netherlands 2. 2 RecSys ’13, Hong Kong, China, Oct. 12, 2013 Who are we? Alexandros, Linas Yue • Machine Learning • Recommender Systems • Data Mining, Social Networks • Multimedia Indexing & A
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