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: 2026-07-13 06:09:35 UTC; root
Repository: https://wliang10.r-universe.dev
Date/Publication: 2017-02-27 07:41:32 UTC
RemoteUrl: https://github.com/cran/gbts
RemoteRef: HEAD
RemoteSha: 8868614fb94692c4d1088c86685f5715dd147893