Neyman-Pearson Based Feature Selection (NPFS) post-hoc test
Python implementation of NPFS. It is still under development and is not considered stable. Contact [email protected].
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