https://github.com/kapsner/mllrnrs

Learners for the `mlexperiments` R 📦
https://github.com/kapsner/mllrnrs

algorithms experiments glmnet learner lightgbm machine-learning r r-package ranger xgboost

Last synced: 18 days ago
JSON representation

Learners for the `mlexperiments` R 📦

• Host: GitHub
• URL: https://github.com/kapsner/mllrnrs
• Owner: kapsner
• License: gpl-3.0
• Created: 2022-10-04T18:58:23.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-07-11T10:21:52.000Z (11 months ago)
• Last Synced: 2024-10-27T13:55:28.582Z (7 months ago)
• Topics: algorithms, experiments, glmnet, learner, lightgbm, machine-learning, r, r-package, ranger, xgboost
• Language: R
• Homepage: https://github.com/kapsner/mllrnrs/wiki
• Size: 297 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: NEWS.md
  • License: LICENSE.md

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README

        
# mllrnrs

[![](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)

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[![](http://cranlogs.r-pkg.org/badges/grand-total/mllrnrs?color=blue)](https://cran.r-project.org/package=mllrnrs)

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The `mllrnrs` R package ships with additional ML learners for

[`mlexperiments`](https://github.com/kapsner/mlexperiments).

Currently implemented learners are:

| Name | Based on | Description / Tasks |

|----|----|----|

| LearnerGlmnet | `glmnet::glmnet` | General interface to `glmnet` (examples available for families [`binomial`](tests/testthat/test-glmnet_binary.R) , [`multinomial`](tests/testthat/test-glmnet_multiclass.R), and [`regression`](tests/testthat/test-glmnet_regression.R) |

| LearnerLightgbm | `lightgbm::lgb.train` | General interface to `lightgbm` (examples available for objectives [`binary`](tests/testthat/test-lightgbm_binary.R) , [`multiclass`](tests/testthat/test-lightgbm_multiclass.R), and [`regression`](tests/testthat/test-lightgbm_regression.R) |

| LearnerRanger | `ranger::ranger` | General interface to `ranger` (examples available for tasks [`binary`](tests/testthat/test-ranger_binary.R) , [`multiclass`](tests/testthat/test-ranger_multiclass.R), and [`regression`](tests/testthat/test-ranger_regression.R) |

| LearnerXgboost | `xgboost::xgb.train` | General interface to `xgboost` (examples available for objectives [`binary:logistic`](tests/testthat/test-xgboost_binary.R) , [`multi:softprob`](tests/testthat/test-xgboost_multiclass.R), and [`reg:squarederror`](tests/testthat/test-xgboost_regression.R) |

For a short introduction on how to use the learners together with the

`mlexperiments` R package, please visit the [wiki

page](https://github.com/kapsner/mllrnrs/wiki).

Some learner for survival tasks are implemented in the

[`mlsurvlrnrs`](https://github.com/kapsner/mlsurvlrnrs) R package.

## Installation

`mllrnrs` can be installed directly from CRAN:

``` r

install.packages("mllrnrs")

```

To install the development version, run

``` r

install.packages("remotes")

remotes::install_github("kapsner/mllrnrs")

```