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author | Ricardo Wurmus <rekado@elephly.net> | 2023-06-02 19:53:47 +0200 |
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committer | Ricardo Wurmus <rekado@elephly.net> | 2023-06-02 19:54:27 +0200 |
commit | 76eda50717c38a59f99c791969ed9a0918106e7e (patch) | |
tree | 19ae22db99ba600df8213644b10b9edf2519357e /gnu/packages/machine-learning.scm | |
parent | f09944461f97537364231ff213a84faadbfb5fe6 (diff) | |
download | guix-76eda50717c38a59f99c791969ed9a0918106e7e.tar.gz |
gnu: Add r-rcppml/devel.
* gnu/packages/machine-learning.scm (r-rcppml/devel): New variable.
Diffstat (limited to 'gnu/packages/machine-learning.scm')
-rw-r--r-- | gnu/packages/machine-learning.scm | 28 |
1 files changed, 28 insertions, 0 deletions
diff --git a/gnu/packages/machine-learning.scm b/gnu/packages/machine-learning.scm index 462e8cf54b..c9bc5e8b68 100644 --- a/gnu/packages/machine-learning.scm +++ b/gnu/packages/machine-learning.scm @@ -48,6 +48,7 @@ #:use-module (guix build-system ocaml) #:use-module (guix build-system pyproject) #:use-module (guix build-system python) + #:use-module (guix build-system r) #:use-module (guix build-system trivial) #:use-module (guix git-download) #:use-module (gnu packages) @@ -602,6 +603,33 @@ value imputation, classifier creation, generalization error estimation and sample proximities between pairs of cases.") (license license:gpl3+))) +(define-public r-rcppml/devel + (let ((commit "e685b3bd7909d3ae74c98f85f81bc0bb679bce23") + (revision "1")) + (package + (name "r-rcppml-devel") + (version (git-version "0.5.6" revision commit)) + (source (origin + (method git-fetch) + (uri (git-reference + (url "https://github.com/zdebruine/RcppML") + (commit commit))) + (file-name (git-file-name name version)) + (sha256 + (base32 + "18ykh9s9h3x79az7qm3pg48iqm0nmkh2wkppc9wx0lq7kjfqm67a")))) + (properties `((upstream-name . "RcppML"))) + (build-system r-build-system) + (propagated-inputs (list r-matrix r-rcpp)) + (native-inputs (list r-knitr)) + (home-page "https://github.com/zdebruine/RcppML") + (synopsis "Rcpp machine learning Library") + (description + "This package provides fast machine learning algorithms including +matrix factorization and divisive clustering for large sparse and dense +matrices.") + (license license:gpl3+)))) + (define-public openfst (package (name "openfst") |