gnu: Add python-scikit-rebate.

* gnu/packages/machine-learning.scm (python-scikit-rebate): New variable.

gnu/packages/machine-learning.scm

@@ -867,6 +867,35 @@ data analysis.")
                  (base32
                   "08zbzi8yx5wdlxfx9jap61vg1malc9ajf576w7a0liv6jvvrxlpj")))))))
 
+(define-public python-scikit-rebate
+  (package
+    (name "python-scikit-rebate")
+    (version "0.6")
+    (source (origin
+              (method url-fetch)
+              (uri (pypi-uri "skrebate" version))
+              (sha256
+               (base32
+                "1h7qs9gjxpzqabzhb8rmpv3jpmi5iq41kqdibg48299h94iikiw7"))))
+    (build-system python-build-system)
+    ;; Pandas is only needed to run the tests.
+    (native-inputs
+     `(("python-pandas" ,python-pandas)))
+    (propagated-inputs
+     `(("python-numpy" ,python-numpy)
+       ("python-scipy" ,python-scipy)
+       ("python-scikit-learn" ,python-scikit-learn)
+       ("python-joblib" ,python-joblib)))
+    (home-page "https://epistasislab.github.io/scikit-rebate/")
+    (synopsis "Relief-based feature selection algorithms for Python")
+    (description "Scikit-rebate is a scikit-learn-compatible Python
+implementation of ReBATE, a suite of Relief-based feature selection algorithms
+for Machine Learning.  These algorithms excel at identifying features that are
+predictive of the outcome in supervised learning problems, and are especially
+good at identifying feature interactions that are normally overlooked by
+standard feature selection algorithms.")
+    (license license:expat)))
+
 (define-public python-autograd
   (let* ((commit "442205dfefe407beffb33550846434baa90c4de7")
          (revision "0")