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Can feature information interaction help for information fusion in multimedia problems?

Kludas, Jana ; Bruno, Eric ; Marchand-Maillet, Stéphane

In: Multimedia Tools and Applications, 2009, vol. 42, no. 1, p. 57-71

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    Titre
    • Can feature information interaction help for information fusion in multimedia problems?
    Auteur
    • Kludas, Jana. CUI, University of Geneva, 7 route de Drize, 1227, Carouge, Switzerland
    • Bruno, Eric. CUI, University of Geneva, 7 route de Drize, 1227, Carouge, Switzerland
    • Marchand-Maillet, Stéphane. CUI, University of Geneva, 7 route de Drize, 1227, Carouge, Switzerland
    Type de document
    • Postprint
    Langue
    • Anglais
    Publié dans
    • Multimedia Tools and Applications, 2009, vol. 42, no. 1, p. 57-71. Springer US; http://www.springer-ny.com
    Autre version électronique
    Identifiant OAI-PMH
    • oai:doc.rero.ch:316461
    Summary
    This article presents the information-theoretic based feature information interaction, a measure that can describe complex feature dependencies in multivariate settings. According to the theoretical development, feature interactions are more accurate than current, bivariate dependence measures due to their stable and unambiguous definition. In experiments with artificial and real data we compare first the empirical dependency estimates of correlation, mutual information and 3-way feature interaction. Then, we present feature selection and classification experiments that show superior performance of interactions over bivariate dependence measures for the artificial data, for real world data this goal is not achieved yet