{
    "info": {
        "author": "Alexander Fabisch",
        "author_email": "afabisch@googlemail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "Operating System :: MacOS",
            "Operating System :: Microsoft :: Windows",
            "Operating System :: POSIX",
            "Operating System :: Unix",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
            "Topic :: Scientific/Engineering",
            "Topic :: Software Development"
        ],
        "description": "===\ngmr\n===\n\n.. image:: https://api.travis-ci.org/AlexanderFabisch/gmr.png?branch=master\n   :target: https://travis-ci.org/AlexanderFabisch/gmr\n   :alt: Travis\n.. image:: https://landscape.io/github/AlexanderFabisch/gmr/master/landscape.svg?style=flat\n   :target: https://landscape.io/github/AlexanderFabisch/gmr/master\n   :alt: Code Health\n\nGaussian Mixture Models (GMMs) for clustering and regression in Python.\n\nSource code repository: https://github.com/AlexanderFabisch/gmr\n\nExample\n-------\n\nEstimate GMM from samples and sample from GMM::\n\n    from gmr import GMM\n\n    gmm = GMM(n_components=3, random_state=random_state)\n    gmm.from_samples(X)\n    X_sampled = gmm.sample(100)\n\n\nFor more details, see::\n\n    help(gmr)\n\nInstallation\n------------\n\nInstall from `PyPI`_::\n\n    sudo pip install gmr\n\nor from source::\n\n    sudo python setup.py install\n\n.. _PyPi: https://pypi.python.org/pypi",
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        "license": "new BSD",
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        "summary": "Gaussian Mixture Regression",
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