gbts: Hyperparameter Search for Gradient Boosted Trees
Waley W. J. Liang · 2016
An implementation of hyperparameter optimization for Gradient Boosted Trees on binary classification and regression problems. The current version provides two optimization methods: Bayesian optimization and random search. Instead of giving the single best model, the final output is an ensemble of Gradient Boosted Trees constructed via the method of ensemble selection.