15 October 2012 Optimization of support vector machine hyperparameters using radius/margin bound
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Proceedings Volume 8454, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2012; 845423 (2012) https://doi.org/10.1117/12.2002318
Event: Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2012, 2012, Wilga, Poland
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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Stanisław Jankowski, Stanisław Jankowski, Wojciech Sadurski, Wojciech Sadurski, } "Optimization of support vector machine hyperparameters using radius/margin bound", Proc. SPIE 8454, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2012, 845423 (15 October 2012); doi: 10.1117/12.2002318; https://doi.org/10.1117/12.2002318
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