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Feature Selection by Eigenvector Centrality

version 4.1.0.0 (748 KB) by Giorgio
Feature Selection by Eigenvector Centrality for Matlab - Updates 2016

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Updated 21 Dec 2016

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

BibTex
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@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}}
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Cite As

Giorgio (2020). Feature Selection by Eigenvector Centrality (https://www.mathworks.com/matlabcentral/fileexchange/54764-feature-selection-by-eigenvector-centrality), MATLAB Central File Exchange. Retrieved .

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MATLAB Release Compatibility
Created with R2015a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Acknowledgements

Inspired by: Infinite Feature Selection, Feature Selection Library

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