| Type de publication : |
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Articles dans des revues avec comité de lecture |
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| Domaine : |
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| Titre : |
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On the estimation of the latent discriminative subspace in the Fisher-EM algorithm |
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| Auteur(s) : |
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Charles Bouveyron ( ) 1, Camille Brunet () 2 |
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| Laboratoire : |
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| Résumé : |
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The Fisher-EM algorithm has been recently proposed in [2] for the simultaneous visualization and clustering of high-dimensional data. It is based on a discriminative latent mixture model which fits the data into a latent discriminative subspace with an intrinsic dimension lower than the dimension of the original space. The Fisher-EM algorithm includes an F-step which estimates the projection matrix whose columns span the discriminative latent space. This matrix is estimated via an optimization problem which is solved using a Gram-Schmidt procedure in the original algorithm. Unfortunately, this procedure suffers in some case from numerical instabilities which may result in a deterioration of the visualization quality or the clustering accuracy. Two alternatives for estimating the latent subspace are proposed to overcome this limitation. The optimization problem of the F-step is first recasted as a regression-type problem and then reformulated such that the solution can be approximated with a SVD. Experiments on simulated and real datasets show the improvement of the proposed alternatives for both the visualization and the clustering of data. |
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Langue du texte
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Anglais |
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Date de production,
écriture : |
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2011 |
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| Journal : |
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Journal de la Société Française de Statistique |
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| Audience : |
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internationale |
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| Date de publication : |
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2011 |
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| Volume : |
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152 |
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| Numéro : |
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3 |
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| Page, identifiant, ... : |
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98-115 |
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