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