PerTurbo: a new classification algorithm based on the spectrum perturbations of the Laplace-Beltrami operator

Abstract : PerTurbo, an original, non-parametric and efficient classification method is presented here. In our framework, the manifold of each class is characterized by its Laplace-Beltrami operator, which is evaluated with classical methods involving the graph Laplacian. The classification criterion is established thanks to a measure of the magnitude of the spectrum perturbation of this operator. The first experiments show good performances against classical algorithms of the state-of-the-art. Moreover, from this measure is derived an efficient policy to design sampling queries in a context of active learning. Performances collected over toy examples and real world datasets assess the qualities of this strategy.
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Communication dans un congrès
ECML-PKDD 2011, 2011, Greece. 2011
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https://hal.archives-ouvertes.fr/hal-00599684
Contributeur : Thomas Burger <>
Soumis le : vendredi 10 juin 2011 - 15:48:42
Dernière modification le : jeudi 12 février 2015 - 17:04:45

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  • HAL Id : hal-00599684, version 1

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Nicolas Courty, Thomas Burger, Laurent Johann. PerTurbo: a new classification algorithm based on the spectrum perturbations of the Laplace-Beltrami operator. ECML-PKDD 2011, 2011, Greece. 2011. <hal-00599684>

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