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author | Nicolas Goaziou <mail@nicolasgoaziou.fr> | 2019-06-18 17:58:31 +0200 |
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committer | Nicolas Goaziou <mail@nicolasgoaziou.fr> | 2019-06-18 17:58:31 +0200 |
commit | d60b064d47a1620754b24fd52722ca77a361b8aa (patch) | |
tree | ea6420c85b053d404f8bf9478770f700c7dce722 /gnu | |
parent | 2e8c912fdc1b17b7bd1cec0c346b401d3979928f (diff) | |
download | patches-d60b064d47a1620754b24fd52722ca77a361b8aa.tar patches-d60b064d47a1620754b24fd52722ca77a361b8aa.tar.gz |
gnu: Add python-iml.
* gnu/packages/machine-learning.scm (python-iml): New variable.
Diffstat (limited to 'gnu')
-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 505cc88f4b..245ccb999b 100644 --- a/gnu/packages/machine-learning.scm +++ b/gnu/packages/machine-learning.scm @@ -10,6 +10,7 @@ ;;; Copyright © 2018 Fis Trivial <ybbs.daans@hotmail.com> ;;; Copyright © 2018 Julien Lepiller <julien@lepiller.eu> ;;; Copyright © 2018 Björn Höfling <bjoern.hoefling@bjoernhoefling.de> +;;; Copyright © 2019 Nicolas Goaziou <mail@nicolasgoaziou.fr> ;;; ;;; This file is part of GNU Guix. ;;; @@ -1753,3 +1754,30 @@ API for beginners that allows users to build models quickly by plugging together building blocks and a subclassing API with an imperative style for advanced research.") (license license:asl2.0))) + +(define-public python-iml + (package + (name "python-iml") + (version "0.6.2") + (source + (origin + (method url-fetch) + (uri (pypi-uri "iml" version)) + (sha256 + (base32 + "1k8szlpm19rcwcxdny9qdm3gmaqq8akb4xlvrzyz8c2d679aak6l")))) + (build-system python-build-system) + (propagated-inputs + `(("ipython" ,python-ipython) + ("nose" ,python-nose) + ("numpy" ,python-numpy) + ("pandas" ,python-pandas) + ("scipy" ,python-scipy))) + (home-page "http://github.com/interpretable-ml/iml") + (synopsis "Interpretable Machine Learning (iML) package") + (description "Interpretable ML (iML) is a set of data type objects, +visualizations, and interfaces that can be used by any method designed to +explain the predictions of machine learning models (or really the output of +any function). It currently contains the interface and IO code from the Shap +project, and it will potentially also do the same for the Lime project.") + (license license:expat))) |