A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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from setuptools import setup, find_packages
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def calculate_version():
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initpy = open('tpot/_version.py').read().split('\n')
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version = list(filter(lambda x: '__version__' in x, initpy))[0].split('\'')[1]
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return version
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package_version = calculate_version()
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setup(
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name='TPOT',
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version=package_version,
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author='Randal S. Olson',
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author_email='rso@randalolson.com',
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packages=find_packages(),
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url='https://github.com/EpistasisLab/tpot',
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license='GNU/LGPLv3',
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entry_points={'console_scripts': ['tpot=tpot:main', ]},
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description=('Tree-based Pipeline Optimization Tool'),
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long_description='''
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A Python tool that automatically creates and optimizes machine learning pipelines using genetic programming.
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Contact
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=============
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If you have any questions or comments about TPOT, please feel free to contact us via:
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E-mail: ttle@pennmedicine.upenn.edu or weixuanf@pennmedicine.upenn.edu
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or Twitter: https://twitter.com/trang1618 or https://twitter.com/WeixuanFu
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This project is hosted at https://github.com/EpistasisLab/tpot
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''',
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zip_safe=True,
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install_requires=['numpy>=1.16.3',
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'scipy>=1.3.1',
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'scikit-learn>=0.22.0',
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'deap>=1.2',
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'update_checker>=0.16',
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'tqdm>=4.36.1',
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'stopit>=1.1.1',
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'pandas>=0.24.2',
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'joblib>=0.13.2',
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'xgboost>=1.1.0'],
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extras_require={
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'skrebate': ['skrebate>=0.3.4'],
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'mdr': ['scikit-mdr>=0.4.4'],
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'dask': ['dask>=0.18.2',
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'distributed>=1.22.1',
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'dask-ml>=1.0.0'],
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'torch': ['torch==1.3.1'],
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'imblearn': ['imbalanced-learn>=0.7.0']
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},
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classifiers=[
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'Intended Audience :: Science/Research',
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'License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)',
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'Programming Language :: Python :: 3.5',
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'Programming Language :: Python :: 3.6',
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'Programming Language :: Python :: 3.7',
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'Topic :: Scientific/Engineering :: Artificial Intelligence'
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],
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keywords=['pipeline optimization', 'hyperparameter optimization', 'data science', 'machine learning', 'genetic programming', 'evolutionary computation'],
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)
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