Package: gbts
Type: Package
Title: Hyperparameter Search for Gradient Boosted Trees
Version: 1.2.0
Date: 2017-02-26
Author: Waley W. J. Liang
Maintainer: Waley W. J. Liang <wliang10@gmail.com>
Description: 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.
License: GPL (>= 2) | file LICENSE
LazyData: true
Imports: doParallel, doRNG, foreach, gbm, earth
Depends: R (>= 3.3.0)
Suggests: testthat
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2017-02-27 06:57:09 UTC; wl
Repository: CRAN
Date/Publication: 2017-02-27 08:41:32
Built: R 4.6.0; ; 2026-04-27 17:08:22 UTC; unix
