fairml 0.1.1.5rc2

Module for measuring feature dependence for black-box models

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FairML: Auditing Black-Box Predictive Models
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FairML is a python toolbox auditing the machine learning models for
bias.

Description
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Predictive models are increasingly been deployed for the purpose of
determining access to services such as credit, insurance, and
employment. Despite societal gains in efficiency and productivity
through deployment of these models, potential systemic flaws have not
been fully addressed, particularly the potential for unintentional
discrimination. This discrimination could be on the basis of race,
gender, religion, sexual orientation, or other characteristics. This
project addresses the question: how can an analyst determine the
relative significance of the inputs to a black-box predictive model in
order to assess the model’s fairness (or discriminatory extent)?