Feature Selection by Eigenvector Centrality
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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Citation pour cette source
Giorgio (2024). Feature Selection by Eigenvector Centrality (https://www.mathworks.com/matlabcentral/fileexchange/54764-feature-selection-by-eigenvector-centrality), MATLAB Central File Exchange. Récupéré le .
Compatibilité avec les versions de MATLAB
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Inspiré par : Infinite Feature Selection, Feature Selection Library
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ECFS2016/
ECFS2016/lib/
ECFS2016/lib/@algorithm/
ECFS2016/lib/@data/
ECFS2016/lib/@distance/
ECFS2016/lib/@fisher/
ECFS2016/lib/@kernel/
ECFS2016/lib/@l0/
ECFS2016/lib/@loss/
ECFS2016/lib/@rfe/
ECFS2016/lib/@svm/
ECFS2016/methods/
Version | Publié le | Notes de version | |
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4.1.0.0 | + documentation |
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3.9.0.0 | [1] InfFS
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3.0.0.0 | - Added new method: Features Selection via Eigenvector Centrality (ECFS) 2016
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2.2.0.0 | Added 9 more feature selection methods from recent literature (2016) |
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1.6.0.0 | http://www.mathworks.com/matlabcentral/fileexchange/56815-feature-selection-library |
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1.5.0.0 | Demo file Added |