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Pollutes documents with terms biased on specific geners

Project description

Document Polluter

Overview

Document Polluter replaces gendered words in documents to create test data for machine learning models in order to identify bias.

Checkout the examples in the interactive notebook.

Installation

document-polluter is available on PyPI

http://pypi.python.org/pypi/document-polluter

Install via pip

$ pip install document-polluter

Install via easy_install

$ easy_install document-polluter

Install from repo

git repo <https://github.com/gregology/document-polluter>

$ git clone --recursive git://github.com/gregology/document-polluter.git
$ cd document-polluter
$ python setup.py install

Basic usage

>>> from document_polluter import DocumentPolluter
>>> documents = ['she shouted', 'my son', 'the parent']
>>> dp = DocumentPolluter(documents=documents, genre='gender')
>>> print(dp.polluted_documents['female'])
['she shouted', 'my daughter', 'the mother']

Running Test

$ python document_polluter/tests.py

Project details


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Source Distribution

document-polluter-0.0.7.tar.gz (3.8 kB view hashes)

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