{
    "info": {
        "author": "Federico Amato",
        "author_email": "federico.amato@unil.ch",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3.6",
            "Topic :: Software Development :: Build Tools"
        ],
        "description": "",
        "description_content_type": "",
        "docs_url": null,
        "download_url": "https://github.com/federhub/pyGRNN/archive/v0.1.tar.gz",
        "downloads": {
            "last_day": -1,
            "last_month": -1,
            "last_week": -1
        },
        "home_page": "https://github.com/federhub/pyGRNN",
        "keywords": "Machine Learning,General Regression Neural Network,Kernel Regression,Feature Selection",
        "license": "MIT",
        "maintainer": "",
        "maintainer_email": "",
        "name": "pyGRNN",
        "package_url": "https://pypi.org/project/pyGRNN/",
        "platform": "",
        "project_url": "https://pypi.org/project/pyGRNN/",
        "project_urls": {
            "Download": "https://github.com/federhub/pyGRNN/archive/v0.1.tar.gz",
            "Homepage": "https://github.com/federhub/pyGRNN"
        },
        "release_url": "https://pypi.org/project/pyGRNN/v0.1/",
        "requires_dist": null,
        "requires_python": "",
        "summary": "Python implementation of General Regression Neural Network (Nadaraya-Watson Estimator). A Feature Selection module based on GRNN is also provided",
        "version": "v0.1"
    },
    "last_serial": 5911220,
    "releases": {
        "v0.1": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "0306a9e1177855bbe3af866b441bed26",
                    "sha256": "276f46493a58290d0a843219853129befd2c4271b380aaca504b230007dfc21d"
                },
                "downloads": -1,
                "filename": "pyGRNN-v0.1.tar.gz",
                "has_sig": false,
                "md5_digest": "0306a9e1177855bbe3af866b441bed26",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 9536,
                "upload_time": "2019-10-01T09:05:26",
                "url": "https://files.pythonhosted.org/packages/c9/57/8ed5b90f5cd7f3effc898e7752f6a4616f994bd21953ddf50a6a942bb994/pyGRNN-v0.1.tar.gz"
            }
        ]
    },
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "md5": "0306a9e1177855bbe3af866b441bed26",
                "sha256": "276f46493a58290d0a843219853129befd2c4271b380aaca504b230007dfc21d"
            },
            "downloads": -1,
            "filename": "pyGRNN-v0.1.tar.gz",
            "has_sig": false,
            "md5_digest": "0306a9e1177855bbe3af866b441bed26",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 9536,
            "upload_time": "2019-10-01T09:05:26",
            "url": "https://files.pythonhosted.org/packages/c9/57/8ed5b90f5cd7f3effc898e7752f6a4616f994bd21953ddf50a6a942bb994/pyGRNN-v0.1.tar.gz"
        }
    ]
}