Package: mllrnrs 0.0.4

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.

Authors:Lorenz A. Kapsner [cre, aut, cph]

mllrnrs_0.0.4.tar.gz
mllrnrs_0.0.4.zip(r-4.5)mllrnrs_0.0.4.zip(r-4.4)mllrnrs_0.0.4.zip(r-4.3)
mllrnrs_0.0.4.tgz(r-4.4-any)mllrnrs_0.0.4.tgz(r-4.3-any)
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mllrnrs.pdf |mllrnrs.html✨
mllrnrs/json (API)

# Install 'mllrnrs' in R:
install.packages('mllrnrs', repos = c('https://kapsner.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/kapsner/mllrnrs/issues

On CRAN:

algorithmsexperimentsglmnetlearnerlightgbmmachine-learningrangerxgboost

6.52 score 1 stars 1 packages 26 scripts 289 downloads 4 exports 76 dependencies

Last updated 5 months agofrom:d5e430689e. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 02 2024
R-4.5-winOKNov 02 2024
R-4.5-linuxOKNov 02 2024
R-4.4-winOKNov 02 2024
R-4.4-macOKNov 02 2024
R-4.3-winOKNov 02 2024
R-4.3-macOKNov 02 2024

Exports:LearnerGlmnetLearnerLightgbmLearnerRangerLearnerXgboost

Dependencies:backportsbase64encbslibcachemcheckmatecliclustercodetoolscolorspacecrayondata.tabledigestdoParallelevaluatefansifarverfastmapfontawesomeforeachforeignFormulafsggplot2gluegridExtragtablehighrHmischmshtmlTablehtmltoolshtmlwidgetsisobanditeratorsjquerylibjsonlitekdryknitrlabelinglatticelifecyclemagrittrMASSMatrixmemoisemgcvmimemlexperimentsmunsellnlmennetpillarpkgconfigprettyunitsprogressR6rappdirsRColorBrewerrlangrmarkdownrpartrstudioapisassscalessplitToolsstringistringrtibbletinytexutf8vctrsviridisviridisLitewithrxfunyaml

glmnet: Binary Classification

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Last update: 2024-05-29
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glmnet: Multiclass Classification

Rendered frommllrnrs_glmnet_multiclass.qmdusingquarto::htmlon Nov 02 2024.

Last update: 2024-05-29
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glmnet: Regression

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Last update: 2024-05-29
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lightgbm: Binary Classification

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Last update: 2024-05-29
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lightgbm: Multiclass Classification

Rendered frommllrnrs_lightgbm_multiclass.qmdusingquarto::htmlon Nov 02 2024.

Last update: 2024-05-29
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lightgbm: Regression

Rendered frommllrnrs_lightgbm_regression.qmdusingquarto::htmlon Nov 02 2024.

Last update: 2024-05-29
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ranger: Binary Classification

Rendered frommllrnrs_ranger_binary.qmdusingquarto::htmlon Nov 02 2024.

Last update: 2024-05-29
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ranger: Multiclass Classification

Rendered frommllrnrs_ranger_multiclass.qmdusingquarto::htmlon Nov 02 2024.

Last update: 2024-05-29
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ranger: Regression

Rendered frommllrnrs_ranger_regression.qmdusingquarto::htmlon Nov 02 2024.

Last update: 2024-05-29
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xgboost: Binary Classification

Rendered frommllrnrs_xgboost_binary.qmdusingquarto::htmlon Nov 02 2024.

Last update: 2024-05-29
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xgboost: Multiclass Classification

Rendered frommllrnrs_xgboost_multiclass.qmdusingquarto::htmlon Nov 02 2024.

Last update: 2024-05-29
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xgboost: Regression

Rendered frommllrnrs_xgboost_regression.qmdusingquarto::htmlon Nov 02 2024.

Last update: 2024-05-29
Started: 2024-05-29