Learning Nonlinear Functions Using Regularized Greedy Forest

5 Sep 2011 Rie Johnson Tong Zhang

We consider the problem of learning a forest of nonlinear decision rules with general loss functions. The standard methods employ boosted decision trees such as Adaboost for exponential loss and Friedman's gradient boosting for general loss... (read more)

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