CRAN/E | gbts

gbts

Hyperparameter Search for Gradient Boosted Trees

Installation

About

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.

Key Metrics

Version 1.2.0
R ≥ 3.3.0
Published 2017-02-27 2608 days ago
Needs compilation? no
License GPL-2
License GPL-3
License File
CRAN checks gbts results

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Maintainer

Maintainer

Waley W. J. Liang

wliang10@gmail.com

Authors

Waley W. J. Liang

Material

README
NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

gbts archive

Depends

R ≥ 3.3.0

Imports

doParallel
doRNG
foreach
gbm
earth

Suggests

testthat