Optimization of support vector machine hyperparameters using radius/margin bound
Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE2012Vol. 8454, pp. 845423–845423
Abstract
The paper presents the method of tuning the support vector machine hyperparameters by minimizing an estimate of the leave-one-out error known as radius/margin bound. The quality of the method, in terms of classification accuracy and generalization rate was tested against an exhaustive grid-search in hyperparameter space using a 2- dimensional Banana dataset.
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