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A fast two-stage classification method of support vector machines
2008
2008 International Conference on Information and Automation
Classification of high-dimensional data generally requires enormous processing time. In this paper, we present a fast two-stage method of support vector machines, which includes a feature reduction algorithm and a fast multiclass method. First, principal component analysis is applied to the data for feature reduction and decorrelation, and then a feature selection method is used to further reduce feature dimensionality. The criterion based on Bhattacharyya distance is revised to get rid of
doi:10.1109/icinfa.2008.4608121
fatcat:bb4via74efc3djwwgxji7kgmuq