diff options
| -rw-r--r-- | gnu/packages/machine-learning.scm | 50 |
1 files changed, 49 insertions, 1 deletions
diff --git a/gnu/packages/machine-learning.scm b/gnu/packages/machine-learning.scm index b35e9b72c6..cfeb1daf63 100644 --- a/gnu/packages/machine-learning.scm +++ b/gnu/packages/machine-learning.scm @@ -23,7 +23,12 @@ #:use-module (guix download) #:use-module (guix build-system gnu) #:use-module (gnu packages) - #:use-module (gnu packages python)) + #:use-module (gnu packages boost) + #:use-module (gnu packages compression) + #:use-module (gnu packages gcc) + #:use-module (gnu packages maths) + #:use-module (gnu packages python) + #:use-module (gnu packages xml)) (define-public libsvm (package @@ -96,3 +101,46 @@ classification.") (inputs `(("python" ,python))) (synopsis "Python bindings of libSVM"))) + +(define-public randomjungle + (package + (name "randomjungle") + (version "2.1.0") + (source + (origin + (method url-fetch) + (uri (string-append + "http://www.imbs-luebeck.de/imbs/sites/default/files/u59/" + "randomjungle-" version ".tar_.gz")) + (sha256 + (base32 + "12c8rf30cla71swx2mf4ww9mfd8jbdw5lnxd7dxhyw1ygrvg6y4w")))) + (build-system gnu-build-system) + (arguments + `(#:configure-flags + (list (string-append "--with-boost=" + (assoc-ref %build-inputs "boost"))) + #:phases + (modify-phases %standard-phases + (add-before + 'configure 'set-CXXFLAGS + (lambda _ + (setenv "CXXFLAGS" "-fpermissive ") + #t))))) + (inputs + `(("boost" ,boost) + ("gsl" ,gsl) + ("libxml2" ,libxml2) + ("zlib" ,zlib))) + (native-inputs + `(("gfortran" ,gfortran-4.8))) + (home-page "http://www.imbs-luebeck.de/imbs/de/node/227/") + (synopsis "Implementation of the Random Forests machine learning method") + (description + "Random Jungle is an implementation of Random Forests. It is supposed to +analyse high dimensional data. In genetics, it can be used for analysing big +Genome Wide Association (GWA) data. Random Forests is a powerful machine +learning method. Most interesting features are variable selection, missing +value imputation, classifier creation, generalization error estimation and +sample proximities between pairs of cases.") + (license license:gpl3+))) |