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    "info": {
        "author": "Picatureanu Nicusor",
        "author_email": "nicolaepicatureanu@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Software Development :: Libraries :: Python Modules",
            "Topic :: Text Processing :: General"
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        "description": "Weka - Python wrapper for Weka classifiers\n==========================================\n\nOverview\n--------\n\nProvides a convenient wrapper for calling Weka classifiers from Python.\n\nInstallation\n------------\n\nFirst install the Weka and LibSVM Java libraries. On Debian/Ubuntu this is simply:\n\n    sudo apt-get install weka libsvm-java\n\nThen install the Python package with pip:\n\n    sudo pip install pywekaclassifiers\n\nUsage\n-----\n\nTrain and test a Weka classifier by instantiating the Classifier class,\npassing in the name of the classifier you want to use:\n\n    from pywekaclassifiers.classifiers import Classifier\n    c = Classifier(name='weka.classifiers.lazy.IBk', ckargs={'-K':1})\n    c.train('training.arff')\n    predictions = c.predict('query.arff')\n\nAlternatively, you can instantiate the classifier by calling its name directly:\n\n    from pywekaclassifiers.classifiers import IBk\n    c = IBk(K=1)\n    c.train('training.arff')\n    predictions = c.predict('query.arff')\n\nThe instance contains Weka's serialized model, so the classifier can be easily\npickled and unpickled like any normal Python instance:\n\n    c.save('myclassifier.pkl')\n    c = Classifier.load('myclassifier.pkl')\n    predictions = c.predict('query.arff')\n\nDevelopment\n-----------\n\nTests require the Python development headers to be installed, which you can install on Ubuntu with:\n\n    sudo apt-get install python-dev python3-dev python3.4-dev\n\nTo run unittests across multiple Python versions, install:\n\n    sudo apt-get install python3.4-minimal python3.4-dev python3.5-minimal python3.5-dev\n\nTo run all [tests](http://tox.readthedocs.org/en/latest/):\n\n    export TESTNAME=; tox\n\nTo run tests for a specific environment (e.g. Python 2.7):\n\n    export TESTNAME=; tox -e py27\n\nTo run a specific test:\n\n    export TESTNAME=.test_IBk; tox -e py27\n\n\n",
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        "home_page": "https://github.com/Nicusor97/PyWekaClassifiers.git",
        "keywords": "",
        "license": "MIT License",
        "maintainer": "",
        "maintainer_email": "",
        "name": "pywekaclassifiers",
        "package_url": "https://pypi.org/project/pywekaclassifiers/",
        "platform": "OS Independent",
        "project_url": "https://pypi.org/project/pywekaclassifiers/",
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        "summary": "A Python wrapper for the Weka data mining library.",
        "version": "0.0.3"
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