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The training of Support Vector Machine (SVM) is an optimization problem of quadratic programming which can not be applied to the online training in real time applications or time-variant data source. The online algorithms proposed by other researchers are with high computational complexity and slow training speed. This manuscript combines the projection gradient and adaptive natural gradient. It proposes...
A novel support vector machine (SVM) with weighted features is proposed. To assign appropriate weights for each feature, a mutual information (MI) based approach is presented. Although the calculation of feature weights may add an extra computational cost, the proposed method generally exhibits better generalization performance over the traditional SVM. The numerical studies on one synthetic and five...
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