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| author | Wiktor Żelazny <wz@freeshell.de> | 2020-12-29 13:41:21 +0100 |
|---|---|---|
| committer | Ricardo Wurmus <rekado@elephly.net> | 2020-12-29 14:39:55 +0100 |
| commit | 7ba7881af6f5effd1a553617875bb522e31cfccd (patch) | |
| tree | 37f21162cd3ed8a9401c5bad5a4a0a97704f6311 /gnu | |
| parent | b32b625f0ab44fbd07804359979995cd3647712b (diff) | |
| download | guix-patches-7ba7881af6f5effd1a553617875bb522e31cfccd.tar guix-patches-7ba7881af6f5effd1a553617875bb522e31cfccd.tar.gz | |
gnu: Add r-mlr3.
* gnu/packages/cran.scm (r-mlr3): New variable.
Signed-off-by: Ricardo Wurmus <rekado@elephly.net>
Diffstat (limited to 'gnu')
| -rw-r--r-- | gnu/packages/cran.scm | 34 |
1 files changed, 34 insertions, 0 deletions
diff --git a/gnu/packages/cran.scm b/gnu/packages/cran.scm index 3604ebd06b..10212e2a68 100644 --- a/gnu/packages/cran.scm +++ b/gnu/packages/cran.scm @@ -25485,3 +25485,37 @@ constraints and dependencies for arbitrary algorithms, and to program on such spaces. It also includes statistical designs and random samplers. Objects are implemented as @code{R6} classes.") (license license:lgpl3))) + +(define-public r-mlr3 + (package + (name "r-mlr3") + (version "0.9.0") + (source (origin + (method url-fetch) + (uri (cran-uri "mlr3" version)) + (sha256 + (base32 + "0gg7rrzxwrnpg6sgm0aa6bmfwmqv3d3za0ghnqrnibg33p9ynpgb")))) + (build-system r-build-system) + (propagated-inputs + `(("r-r6" ,r-r6) + ("r-backports" ,r-backports) + ("r-checkmate" ,r-checkmate) + ("r-data-table" ,r-data-table) + ("r-digest" ,r-digest) + ("r-future-apply" ,r-future-apply) + ("r-lgr" ,r-lgr) + ("r-mlbench" ,r-mlbench) + ("r-mlr3measures" ,r-mlr3measures) + ("r-mlr3misc" ,r-mlr3misc) + ("r-paradox" ,r-paradox) + ("r-uuid" ,r-uuid))) + (home-page "https://mlr3.mlr-org.com/") + (synopsis "Machine Learning in R - Next Generation") + (description "@code{mlr3} enables efficient, object-oriented programming +on the building blocks of machine learning. It provides @code{R6} objects for +tasks, learners, resamplings, and measures. The package is geared towards +scalability and larger datasets by supporting parallelization and out-of-memory +data-backends like databases. While @code{mlr3} focuses on the core +computational operations, add-on packages provide additional functionality.") + (license license:lgpl3))) |