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| author | Brett Gilio <brettg@gnu.org> | 2019-12-23 17:28:46 -0600 |
|---|---|---|
| committer | Brett Gilio <brettg@gnu.org> | 2019-12-23 17:28:46 -0600 |
| commit | 5e42d19781abe8d7b3ad28548a1ba35ba196486a (patch) | |
| tree | 72c5d9f81d83ee90888f93b2837a8102fd819e45 /gnu/packages/machine-learning.scm | |
| parent | bff3661726501ed8c79fd4cfcc677b3161377730 (diff) | |
| download | patches-5e42d19781abe8d7b3ad28548a1ba35ba196486a.tar patches-5e42d19781abe8d7b3ad28548a1ba35ba196486a.tar.gz | |
gnu: Add python-umap-learn.
* gnu/packages/machine-learning.scm (python-umap-learn): New variable.
Diffstat (limited to 'gnu/packages/machine-learning.scm')
| -rw-r--r-- | gnu/packages/machine-learning.scm | 29 |
1 files changed, 29 insertions, 0 deletions
diff --git a/gnu/packages/machine-learning.scm b/gnu/packages/machine-learning.scm index d7df30e751..719401d69a 100644 --- a/gnu/packages/machine-learning.scm +++ b/gnu/packages/machine-learning.scm @@ -12,6 +12,7 @@ ;;; Copyright © 2018 Björn Höfling <bjoern.hoefling@bjoernhoefling.de> ;;; Copyright © 2019 Nicolas Goaziou <mail@nicolasgoaziou.fr> ;;; Copyright © 2019 Guillaume Le Vaillant <glv@posteo.net> +;;; Copyright © 2019 Brett Gilio <brettg@gnu.org> ;;; ;;; This file is part of GNU Guix. ;;; @@ -2088,3 +2089,31 @@ number of collective algorithms useful for machine learning applications. These include a barrier, broadcast, and allreduce.") (home-page "https://github.com/facebookincubator/gloo") (license license:bsd-3)))) + +(define-public python-umap-learn + (package + (name "python-umap-learn") + (version "0.3.10") + (source + (origin + (method url-fetch) + (uri (pypi-uri "umap-learn" version)) + (sha256 + (base32 + "02ada2yy6km6zgk2836kg1c97yrcpalvan34p8c57446finnpki1")))) + (build-system python-build-system) + (native-inputs + `(("python-nose" ,python-nose))) + (propagated-inputs + `(("python-numba" ,python-numba) + ("python-numpy" ,python-numpy) + ("python-scikit-learn" ,python-scikit-learn) + ("python-scipy" ,python-scipy))) + (home-page "https://github.com/lmcinnes/umap") + (synopsis + "Uniform Manifold Approximation and Projection") + (description + "Uniform Manifold Approximation and Projection is a dimension reduction +technique that can be used for visualisation similarly to t-SNE, but also for +general non-linear dimension reduction.") + (license license:bsd-3))) |