Feature Selection by Eigenvector Centrality

Version 4.1.0.0 (748 KB) by Giorgio
Feature Selection by Eigenvector Centrality for Matlab - Updates 2016
914 Downloads
Updated 21 Dec 2016

View License

A selection of recent state of the art "feature ranking and selection" methods for Matlab.

BibTex
------------------------------------------------------------------------
@InProceedings{RoffoICCV15,
author={G. Roffo and S. Melzi and M. Cristani},
booktitle={2015 IEEE International Conference on Computer Vision (ICCV)},
title={Infinite Feature Selection},
year={2015},
pages={4202-4210},
keywords={feature extraction;image classification;image filtering;matrix algebra;object recognition;Inf-FS;classification setting;feature learning strategy;filter-based feature selection;infinite feature selection;matrices;object recognition;Benchmark testing;Convergence;Feature extraction;Joining processes;Object recognition;Redundancy;Standards},
doi={10.1109/ICCV.2015.478},
month={Dec}}
------------------------------------------------------------------------

Cite As

Giorgio (2024). Feature Selection by Eigenvector Centrality (https://www.mathworks.com/matlabcentral/fileexchange/54764-feature-selection-by-eigenvector-centrality), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2015a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Categories
Find more on Statistics and Machine Learning Toolbox in Help Center and MATLAB Answers
Acknowledgements

Inspired by: Infinite Feature Selection, Feature Selection Library

Community Treasure Hunt

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

Start Hunting!
Version Published Release Notes
4.1.0.0

+ documentation

3.9.0.0

[1] InfFS
[2] ECFS
[3] mrmr
[4] relieff
[5] mutinffs
[6] fsv
[7] laplacian
[8] mcfs
[9] rfe
[10] L0
[11] fisher
[12] UDFS
[13] llcfs
[14] cfs

3.0.0.0

- Added new method: Features Selection via Eigenvector Centrality (ECFS) 2016
- Updated the Infinite Feature Selection (InfFS) - Strong improvments on ranking accuracy 2016

2.2.0.0

Added 9 more feature selection methods from recent literature (2016)

1.6.0.0

http://www.mathworks.com/matlabcentral/fileexchange/56815-feature-selection-library

1.5.0.0

Demo file Added