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-devel-UCRT: 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-release (x86_64): agtboost_0.9.3.tgz, r-oldrel: agtboost_0.9.3.tgz
Old sources: agtboost archive

Reverse dependencies:

Reverse imports: autostats

Linking:

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