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Descripción
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| We consider the problem of multi-class classification with imbalanced data-sets. To this end, we introduce a cost-sensitive multi-class Boosting algorithm (BAdaCost) based on a generalization of the Boosting margin, termed multi-class cost-sensitive margin. To address the class imbalance we introduce a cost matrix that weighs more hevily the costs of confused classes and a procedure to estimate these costs from the confusion matrix of a standard 0|1-loss classifier. Finally, we evaluate the performance of the approach with synthetic and real data-sets and compare our results with the AdaC2.M1 algorithm. | |
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Internacional
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Si |
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ISSN o ISBN
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978-3-319-19389-2 |
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Entidad relacionada
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Iberian Conference on Pattern Recognition and Image Analysis |
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Nacionalidad Entidad
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Sin nacionalidad |
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Lugar del congreso
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Santiago de Compostela |