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+<?xml version="1.0" encoding="UTF-8"?>
+<!DOCTYPE pkgmetadata SYSTEM "http://www.gentoo.org/dtd/metadata.dtd">
+<pkgmetadata>
+<herd>sci</herd>
+<longdescription lang="en">
+ Milk is a machine learning toolkit in Python.
+ Its focus is on supervised classification with several classifiers
+ available: SVMs (based on libsvm), k-NN, random forests, decision
+ trees. It also performs feature selection. These classifiers can be
+ combined in many ways to form different classification systems.
+ For unsupervised learning, milk supports k-means clustering and
+ affinity propagation.
+ Milk is flexible about its inputs. It optimised for numpy arrays, but
+ can often handle anything (for example, for SVMs, you can use any
+ dataype and any kernel and it does the right thing).
+ There is a strong emphasis on speed and low memory usage. Therefore,
+ most of the performance sensitive code is in C++. This is behind
+ Python-based interfaces for convenience.
+</longdescription>
+<upstream>
+ <remote-id type="pypi">milk</remote-id>
+</upstream>
+</pkgmetadata>