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esafak authored Aug 19, 2016
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.. image:: https://travis-ci.org/esafak/mca.png?branch=master
:target: https://travis-ci.org/esafak/mca

.. image:: https://pypip.in/download/mca/badge.png
:target: https://pypi.python.org/pypi/mca

.. image:: https://pypip.in/license/mca/badge.png
:target: https://github.com/esafak/mca/blob/master/LICENSE


mca is a `Multiple Correspondence Analysis <http://en.wikipedia.org/wiki/Multiple_correspondence_analysis>`_ (MCA) package for python, intended to be used with `pandas <http://pandas.pydata.org/>`_. MCA is a `feature extraction <http://en.wikipedia.org/wiki/Feature_extraction>`_ method; essentially `PCA <http://en.wikipedia.org/wiki/Principal_component_analysis>`_ for `categorical variables <http://en.wikipedia.org/wiki/Categorical_variable>`_. You can use it, for example, to address `multicollinearity <http://en.wikipedia.org/wiki/Multicollinearity>`_ or the `curse of dimensionality <http://en.wikipedia.org/wiki/Curse_of_dimensionality>`_ with big categorical variables.

Installation
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