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A Python interface to the Feature Selection Toolkit, contains JMI, BetaGamma, CMIM, CondMI, DISR, ICAP, and mRMR
Python
branch: master

README.markdown

PyFeast

Python bindings to the FEAST Feature Selection Toolbox..

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About PyFeast

PyFeast is a interface for the FEAST feature selection toolbox, which was originally written in C with a interface to Matlab.

Because Python is also commonly used in computational science, writing bindings to enable researchers to utilize these feature selection algorithms in Python was only natural.

At Drexel University's EESI Lab, we are using PyFeast to create a feature selection tool for the Department of Energy's upcoming KBase platform. We are also integrating a tool that utilizes PyFeast as a script for Qiime users: Qiime Fizzy Branch

Requirements

In order to use the feast module, you will need the following dependencies

Installation

python ./setup.py build
sudo python ./setup.py install

Demonstration

See test/test.py for an example with uniform data and an image data set. The image data set was collected from the digits example in the Scikits-Learn toolbox. Make sure that if you are loading the data from a file and converting the data to a numpy array that you set order="F". This is very important.

Documentation

We have documentation for each of the functions available here

References

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