agtboost: Adaptive and Automatic Gradient Boosting Computations

Fast and automatic gradient tree boosting designed to avoid manual tuning and cross-validation by utilizing an information theoretic approach. This makes the algorithm adaptive to the dataset at hand; it is completely automatic, and with minimal worries of overfitting. Consequently, the speed-ups relative to state-of-the-art implementations can be in the thousands while mathematical and technical knowledge required on the user are minimized.

Version:	0.9.3
Depends:	R (≥ 3.6.0)
Imports:	methods, Rcpp (≥ 1.0.1)
LinkingTo:	Rcpp, RcppEigen
Suggests:	testthat
Published:	2021-11-23
Author:	Berent Ånund Strømnes Lunde
Maintainer:	Berent Ånund Strømnes Lunde <lundeberent at gmail.com>
License:	GPL-3
NeedsCompilation:	yes
Materials:	NEWS
CRAN checks:	agtboost results

Documentation:

Reference manual:

agtboost.pdf

Downloads:

Package source:	agtboost_0.9.3.tar.gz
Windows binaries:	r-devel: agtboost_0.9.3.zip, r-release: agtboost_0.9.3.zip, r-oldrel: agtboost_0.9.3.zip
macOS binaries:	r-release (arm64): agtboost_0.9.3.tgz, r-oldrel (arm64): agtboost_0.9.3.tgz, r-release (x86_64): agtboost_0.9.3.tgz, r-oldrel (x86_64): agtboost_0.9.3.tgz
Old sources:	agtboost archive

Reverse dependencies:

Reverse imports:

autostats

Linking:

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