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"description": "# niacin\n\nA Python library for replacing the missing variation in your data.\n\n[](https://badge.fury.io/py/niacin)\n[](https://travis-ci.org/deniederhut/niacin/)\n[](https://codecov.io/gh/deniederhut/niacin)\n[](https://niacin.readthedocs.io/en/latest/?badge=latest)\n\n\n## Why should I use this?\n\nData collected for model training necessarily undersamples the likely\nvariance in the input space. This library is a collection of tools for\ninserting typical kinds of perturbations to better approximate population\nvariance; and, for creating similar-but-incorrect examples to aid in\nreducing the total size of the hypothesis space. These are commonly known as\nENRICHMENT and NEGATIVE SAMPLING, respectively.\n\n## How do I use this?\n\nFunctions in niacin are separated into submodules for specific data types.\nFunctions expose a similar API, with two input arguments: the data to be\ntransformed, and the probability of applying a specific transformation.\n\nenrichment:\n\n```python\ndata = \"This is the song that never ends and it goes on and on my friends\"\nprint(text.add_misspelling(data, p=1.0))\n```\n\n```output\nThis is teh song tath never ends adn it goes on anbd on my firends\n```\n\nnegative sampling:\n\n```python\ndata = \"This is the song that never ends and it goes on and on my friends\"\nprint(text.add_hypernyms(data, p=1.0))\n```\n\n```output\nThis is the musical composition that never extremity and it exit on and on my person\n```\n\n## How do I install this?\n\nwith `pip`:\n\n```sh\npip install niacin\n```\n\nfrom source:\n\n```sh\ngit clone git@github.com:deniederhut/niacin.git && cd niacin && python setup.py install\n```\n\n\n",
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