The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

mllrnrs: R6-Based ML Learners for 'mlexperiments'

Enhances 'mlexperiments' <https://CRAN.R-project.org/package=mlexperiments> with additional machine learning ('ML') learners. The package provides R6-based learners for the following algorithms: 'glmnet' <https://CRAN.R-project.org/package=glmnet>, 'ranger' <https://CRAN.R-project.org/package=ranger>, 'xgboost' <https://CRAN.R-project.org/package=xgboost>, and 'lightgbm' <https://CRAN.R-project.org/package=lightgbm>. These can be used directly with the 'mlexperiments' R package.

Version:	0.0.3
Depends:	R (≥ 2.10)
Imports:	data.table, kdry, mlexperiments, R6, stats
Suggests:	glmnet, knitr, lightgbm (≥ 4.0.0), lintr, mlbench, mlr3measures, ParBayesianOptimization, ranger, splitTools, testthat (≥ 3.0.1), xgboost
Published:	2024-03-07
Author:	Lorenz A. Kapsner [cre, aut, cph]
Maintainer:	Lorenz A. Kapsner <lorenz.kapsner at gmail.com>
BugReports:	https://github.com/kapsner/mllrnrs/issues
License:	GPL (≥ 3)
URL:	https://github.com/kapsner/mllrnrs
NeedsCompilation:	no
CRAN checks:	mllrnrs results

Documentation:

Reference manual:	mllrnrs.pdf
Vignettes:	glmnet: Binary Classification glmnet: Multiclass Classification glmnet: Regression lightgbm: Binary Classification lightgbm: Multiclass Classification lightgbm: Regression ranger: Binary Classification ranger: Multiclass Classification ranger: Regression xgboost: Binary Classification xgboost: Multiclass Classification xgboost: Regression

Downloads:

Package source:	mllrnrs_0.0.3.tar.gz
Windows binaries:	r-devel: mllrnrs_0.0.3.zip, r-release: mllrnrs_0.0.3.zip, r-oldrel: mllrnrs_0.0.3.zip
macOS binaries:	r-release (arm64): mllrnrs_0.0.3.tgz, r-oldrel (arm64): mllrnrs_0.0.3.tgz, r-release (x86_64): mllrnrs_0.0.3.tgz, r-oldrel (x86_64): mllrnrs_0.0.3.tgz
Old sources:	mllrnrs archive

Reverse dependencies:

Reverse imports:

mlsurvlrnrs

Linking:

Please use the canonical form https://CRAN.R-project.org/package=mllrnrs to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.