File Exchange

image thumbnail

Simple Filter Feature Selection Algorithms

version 1.0.2 (59.5 KB) by Jingwei Too
Simple, fast and ease of implementation. The filter feature selection algorithms include Relief-F, PCC and F-score.


Updated 22 Jul 2020

View Version History

View License

This toolbox contains four commonly used filter feature selection algorithms
(1) Relief-F (RF)
(2) Pearson Correlation Coefficient (PCC)
(3) F-score (FS)
(4) Term Variance (TV)

The "Main" script shows the examples on how to use these filter feature selection programs with the benchmark data set.

Cite As

Jingwei Too (2020). Simple Filter Feature Selection Algorithms (, MATLAB Central File Exchange. Retrieved .

Comments and Ratings (5)

云凯i 杨

Thanks for your sharing!So suprised to get it!

Jingwei Too

Dear Han Yan,

Some researchers do normalization but some do not. In some cases, normalization makes accuracy higher but some do not. You need to test it.

han yan

Do we need to normalize before the feature selection algorithm? Thank you.

Esther Kui

Thank you


Thanks for sharing helpful code.. Kindly, could you refer to the research papers of these algorithms?

MATLAB Release Compatibility
Created with R2018a
Compatible with any release
Platform Compatibility
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Simple Filter Feature Selection Algorithms