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        "author": "Christos Aridas",
        "author_email": "ichkoar@gmail.com",
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            "Topic :: Software Development"
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        "description": "===============================\nDagging\n===============================\n\n.. image:: https://img.shields.io/travis/chkoar/dagging.svg\n        :target: https://travis-ci.org/chkoar/dagging\n\n.. image:: https://codecov.io/gh/chkoar/dagging/branch/master/graph/badge.svg\n  :target: https://codecov.io/gh/chkoar/dagging\n\n.. image:: https://img.shields.io/pypi/v/dagging.svg\n        :target: https://pypi.python.org/pypi/dagging\n\n\nPython package implementing the dagging method\n\n* Free software: 3-clause BSD license\n\nExample\n-------\n\n.. code-block:: python\n\n    from dagging import DaggingClassifier\n    from sklearn.datasets import load_iris \n\n    # Load Iris from from scikit-learn.\n    X, y = load_iris(True)\n\n    model = DaggingClassifier(n_estimators=50,\n                              voting='hard',\n                              random_state=0)\n\n    # Train the model.\n    model.fit(X,y)\n\n    # Accuracy\n    print(model.score(X, y))\n\n\nDependencies\n------------\n\nThe dependency requirements are based on the last scikit-learn release:\n\n* scipy\n* numpy\n* scikit-learn\n\nInstallation\n------------\n\ndagging is currently available on the PyPi's repository and you can\ninstall it via `pip`::\n\n  pip install -U dagging\n\nIf you prefer, you can clone it and run the setup.py file. Use the following\ncommands to get a copy from GitHub and install all dependencies::\n\n  git clone https://github.com/chkoar/dagging.git\n  cd dagging\n  pip install .\n\nOr install using pip and GitHub::\n\n  pip install -U git+https://github.com/chkoar/dagging.git\n\n\n",
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