<gh_stars>10-100
from setuptools import setup, find_packages
# To use a consistent encoding
from codecs import open
from os import path

here = path.abspath(path.dirname(__file__))

# Get the long description from the README file
with open(path.join(here, 'README.md'), encoding='utf-8') as f:
    long_description = f.read()

# Get version number
exec(open('rankpruning/version.py').read())

setup(
    name='rankpruning',
    version=__version__,
    license='MIT',
    long_description=long_description,
    description = 'An algorithm for binary classification with mislabeled training data.',
    url = 'https://github.com/cgnorthcutt/rankpruning',

    # <NAME> (<EMAIL>) was invaluable for testing and added 
    # the cnn_classifier.py which was modififed from keras.
    author = '<NAME>',
    author_email = '<EMAIL>',

    # See https://pypi.python.org/pypi?%3Aaction=list_classifiers
    classifiers=[
      # How mature is this project? Common values are
      #   3 - Alpha
      #   4 - Beta
      #   5 - Production/Stable
      'Development Status :: 3 - Alpha',
      'Intended Audience :: Developers',
      'Topic :: Machine Learning :: Noisy Learning',
       'License :: OSI Approved :: MIT License',

      # We believe this package works will all versions, but we do not guarantee it!
      'Programming Language :: Python :: 2.7',
      # 'Programming Language :: Python :: 3',
      # 'Programming Language :: Python :: 3.2',
      # 'Programming Language :: Python :: 3.3',
      # 'Programming Language :: Python :: 3.4',
      # 'Programming Language :: Python :: 3.5',
    ],

    # What does your project relate to?
    keywords='machine_learning mislabeling classification',

    # You can just specify the packages manually here if your project is
    # simple. Or you can use find_packages().
    packages=find_packages(exclude=['tutorial_and_testing']),

    # List run-time dependencies here.  These will be installed by pip when
    # your project is installed. For an analysis of "install_requires" vs pip's
    # requirements files see:
    # https://packaging.python.org/en/latest/requirements.html
    install_requires=['numpy>=1.11.3', 'scikit-learn>=0.18'],
)
from setuptools import setup, find_packages
# To use a consistent encoding
from codecs import open
from os import path

here = path.abspath(path.dirname(__file__))

# Get the long description from the README file
with open(path.join(here, 'README.md'), encoding='utf-8') as f:
    long_description = f.read()

# Get version number
exec(open('rankpruning/version.py').read())

setup(
    name='rankpruning',
    version=__version__,
    license='MIT',
    long_description=long_description,
    description = 'An algorithm for binary classification with mislabeled training data.',
    url = 'https://github.com/cgnorthcutt/rankpruning',

    # <NAME> (<EMAIL>) was invaluable for testing and added 
    # the cnn_classifier.py which was modififed from keras.
    author = '<NAME>',
    author_email = '<EMAIL>',

    # See https://pypi.python.org/pypi?%3Aaction=list_classifiers
    classifiers=[
      # How mature is this project? Common values are
      #   3 - Alpha
      #   4 - Beta
      #   5 - Production/Stable
      'Development Status :: 3 - Alpha',
      'Intended Audience :: Developers',
      'Topic :: Machine Learning :: Noisy Learning',
       'License :: OSI Approved :: MIT License',

      # We believe this package works will all versions, but we do not guarantee it!
      'Programming Language :: Python :: 2.7',
      # 'Programming Language :: Python :: 3',
      # 'Programming Language :: Python :: 3.2',
      # 'Programming Language :: Python :: 3.3',
      # 'Programming Language :: Python :: 3.4',
      # 'Programming Language :: Python :: 3.5',
    ],

    # What does your project relate to?
    keywords='machine_learning mislabeling classification',

    # You can just specify the packages manually here if your project is
    # simple. Or you can use find_packages().
    packages=find_packages(exclude=['tutorial_and_testing']),

    # List run-time dependencies here.  These will be installed by pip when
    # your project is installed. For an analysis of "install_requires" vs pip's
    # requirements files see:
    # https://packaging.python.org/en/latest/requirements.html
    install_requires=['numpy>=1.11.3', 'scikit-learn>=0.18'],
)
# To use a consistent encoding # Get the long description from the README file # Get version number # <NAME> (<EMAIL>) was invaluable for testing and added # the cnn_classifier.py which was modififed from keras. # See https://pypi.python.org/pypi?%3Aaction=list_classifiers # How mature is this project? Common values are #   3 - Alpha #   4 - Beta #   5 - Production/Stable # We believe this package works will all versions, but we do not guarantee it! # 'Programming Language :: Python :: 3', # 'Programming Language :: Python :: 3.2', # 'Programming Language :: Python :: 3.3', # 'Programming Language :: Python :: 3.4', # 'Programming Language :: Python :: 3.5', # What does your project relate to? # You can just specify the packages manually here if your project is # simple. Or you can use find_packages(). # List run-time dependencies here.  These will be installed by pip when # your project is installed. For an analysis of "install_requires" vs pip's # requirements files see: # https://packaging.python.org/en/latest/requirements.html