https://github.com/scikit-learn-contrib/metric-learn
Revision 2bf0266d9b201cf477cbf20156d06bcc612bd9b4 authored by CJ Carey on 07 November 2015, 22:48:41 UTC, committed by CJ Carey on 07 November 2015, 22:48:41 UTC
1 parent eae4cd5
Tip revision: 2bf0266d9b201cf477cbf20156d06bcc612bd9b4 authored by CJ Carey on 07 November 2015, 22:48:41 UTC
Choosing a better seed + adding note
Choosing a better seed + adding note
Tip revision: 2bf0266
setup.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from setuptools import setup
version = "0.1.1"
setup(name='metric-learn',
version=version,
description='Python implementations of metric learning algorithms',
author=['CJ Carey', 'Yuan Tang'],
author_email='ccarey@cs.umass.edu',
url='http://github.com/all-umass/metric-learn',
license='MIT',
classifiers=[
'Development Status :: 4 - Beta',
'License :: OSI Approved :: MIT License',
'Programming Language :: Python',
'Operating System :: OS Independent',
'Intended Audience :: Science/Research',
'Topic :: Scientific/Engineering'
],
packages=['metric_learn'],
install_requires=[
'numpy',
'scipy',
'scikit-learn',
'six'
],
extras_require=dict(
docs=['sphinx', 'numpydoc'],
demo=['matplotlib'],
),
test_suite='test',
keywords=[
'Metric Learning',
'Large Margin Nearest Neighbor',
'Information Theoretic Metric Learning',
'Sparse Determinant Metric Learning',
'Least Squares Metric Learning',
'Neighborhood Components Analysis'
])
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