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        "description": "Close-k Classifier\n==================\n\nThis repository contains code accompanying\n> [Minimizing Close-k Aggregate Loss Improves Classification](https://arxiv.org/abs/1811.00521)\n>\n> Bryan He, James Zou.\n\nWe provide a Python 3 implementation using the\n[scikit-learn API](http://scikit-learn.org/stable/developers/contributing.html#apis-of-scikit-learn-objects),\nand provide code to reproduce the figures and tables from the paper.\n\nInstallation\n------------\n\nOur package is available on [PyPy](https://pypi.org/project/closek/), and can be installed using\n> pip install -i https://pypi.org/project/ closek\n\nYou can also install this package by cloning the [Github repository](github.com/bryan-he/closek), and running\n> pip install closek\n\nIf you want directly use the implementation in your package, you can also copy\n[closek/closek.py](github.com/bryan-he/closekclosek/closek.py) into your code.\n\nUsage\n-----\n\nAn example of how to use our package is shown in [test.py](github.com/bryan-he/closek/test.py).\n\nGenerating Results from Paper\n-----------------------------\n\nThe code used for the paper is in [experiments](github.com/bryan-he/closek/experiments). See the README\nthere for more details.\n\n\n\n",
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