gbts (1.2.0)

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Hyperparameter Search for Gradient Boosted Trees.

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.

Maintainer: Waley W. J. Liang
Author(s): Waley W. J. Liang

License: GPL (>= 2) | file LICENSE

Uses: doParallel, doRNG, earth, foreach, gbm, testthat

Released over 1 year ago.

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