Sélection des variables optimales par optimisation multi-objective de l'information mutuelle

Abstract : This work proposes an original approach using mutual information and Pareto curve jointly for feature selection. Mutual information is used to estimate dependency criterion between features and classes and redundancy criterion between features taken two by two. Unlike some studies, these criteria are used simultaneously to compute Pareto curve and determine the optimal feature sets. This approach is tested on more reference data. Several clustering algorithms are used to compute classification accuracy. The obtained results show the importance of our tools and its ability to select the best feature sets that give the better description.
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Communication dans un congrès
GRETSI, Sep 2011, Bordeaux, France. pp.1, 2011
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https://hal.archives-ouvertes.fr/hal-00602260
Contributeur : Enguerran Grandchamp <>
Soumis le : mardi 21 juin 2011 - 21:39:17
Dernière modification le : mercredi 29 novembre 2017 - 09:37:40

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  • HAL Id : hal-00602260, version 1

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Enguerran Grandchamp, Olivier Alata, Christian Olivier, Majdi Khoudeir, Mohamed Abadi. Sélection des variables optimales par optimisation multi-objective de l'information mutuelle. GRETSI, Sep 2011, Bordeaux, France. pp.1, 2011. 〈hal-00602260〉

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