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Neyman-Pearson Based Feature Selection (NPFS) post-hoc test

Python implementation of NPFS. It is still under development and is not considered stable. Contact gregory.ditzler@gmail.com.

There are types of feature subset selection problems that require that the size of the subset be specied prior to running the selection algorithm. NPFS works with the decisions of a base subset selection algorithm to determine an appropriate number of features to select given an initial starting point. NPFS uses the FEAST feature selection toolbox; however, the approach is not limited to using the this toolbox.

Module Installation

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

Citing NPFS

  • Gregory Ditzler, Robi Polikar, Gail Rosen, "A Bootstrap Based Neyman–Pearson Test for Identifying Variable Importance," 2014, In press. (link)

Requirements

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

Requirements

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

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