https://github.com/mlr-org/mlr3measures

Performance measures used in mlr3
https://github.com/mlr-org/mlr3measures

machine-learning mlr3 performance-evaluation performance-measures r r-package

Last synced: 2 days ago
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Performance measures used in mlr3

• Host: GitHub
• URL: https://github.com/mlr-org/mlr3measures
• Owner: mlr-org
• License: lgpl-3.0
• Created: 2019-10-04T14:11:29.000Z (about 5 years ago)
• Default Branch: main
• Last Pushed: 2024-09-12T14:11:20.000Z (about 2 months ago)
• Last Synced: 2024-10-13T02:40:54.748Z (26 days ago)
• Topics: machine-learning, mlr3, performance-evaluation, performance-measures, r, r-package
• Language: R
• Homepage: https://mlr3measures.mlr-org.com
• Size: 3.52 MB
• Stars: 13
• Watchers: 10
• Forks: 3
• Open Issues: 5
• Metadata Files:
  • Readme: README.md
  • Changelog: NEWS.md
  • License: LICENSE

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README

        
# mlr3measures

Package website: [release](https://mlr3measures.mlr-org.com/) | [dev](https://mlr3measures.mlr-org.com/dev/)

[![r-cmd-check](https://github.com/mlr-org/mlr3measures/actions/workflows/r-cmd-check.yml/badge.svg)](https://github.com/mlr-org/mlr3measures/actions/workflows/r-cmd-check.yml)

[![CRAN Status](https://www.r-pkg.org/badges/version-ago/mlr3measures)](https://cran.r-project.org/package=mlr3measures)

[![StackOverflow](https://img.shields.io/badge/stackoverflow-mlr3-orange.svg)](https://stackoverflow.com/questions/tagged/mlr3)

[![Mattermost](https://img.shields.io/badge/chat-mattermost-orange.svg)](https://lmmisld-lmu-stats-slds.srv.mwn.de/mlr_invite/)

Implements multiple performance measures for supervised learning.

Includes over 40 measures for regression and classification.

Additionally, meta information about the performance measures can be queried, e.g. what the best and worst possible performances scores are.

Internally, [checkmate](https://CRAN.R-project.org/package=checkmate) is used to check arguments efficiently - no other runtime dependencies.

The [function reference](https://mlr3measures.mlr-org.com/reference/index.html) gives an encompassing overview over implemented measures.

Note that explicitly loading this package is not required if you want to use any of these measures in [mlr3](https://mlr3.mlr-org.com).

Also note that we advise against attaching the package via `library()` to avoid namespace clashes.

Instead, load the namespace via `requireNamespace()` and use the `::` operator.