Fast Correlation-Based Filter (FCBF) selection.

Paper: http://www.public.asu.edu/~huanliu/papers/icml03.pdf

Implementation of the FCBF algorithm.

System requirements

• Requires Python 2.7
• Works on Linux and Mac. No guarantees for other OS, but may work.

Usage

Input file format:

Row: observation vector, Col: Feature/Variable vector

In Python, call

`fcbf_wrapper(inpath, thresh, delim=',', header=False, classAt=-1)`

OR

From command line,

> cd FCBF
> python src/fcbf.py -h
usage: fcbf.py [-h] [-inpath] [-thresh] [-delim] [-header] [-classAt]

Fast Correlation-Based Filter Selection (FCBF)

optional arguments:
  -h, --help  show this help message and exit
  -inpath     Path to input file
  -thresh     SU threshold
  -delim      File delimiter
  -header     Contains header?
  -classAt    Index of class column

> python src/fcbf.py -inpath='./data/lungcancer.csv' -thresh=0.05
Reading file. Please wait ...
Success! Dimensions: 32 x 57
Performing FCBF selection. Please wait ...
Done!

#Features selected: 6
Selected feature indices:
[[  0.32054501  39.        ]
 [  0.32017586  19.        ]
 [  0.19562365  55.        ]
 [  0.15251083   1.        ]
 [  0.12478091   9.        ]
 [  0.07640196   2.        ]]

File saved successfully. Path: ../data/features_lungcancer.csv