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In this paper, we proposed a method to speed up the test phase of SVM based on Feature Vector Selection method (FVS). In the method, the support vectors ...
Apr 24, 2013 · The number of support vectors can be reduced by training with stronger regularization, ie by increasing the hyperparameter C (possibly at a cost in predictive ...
Experiments show that the number of SVs can be reduced from 20% to 99% with only a slight increase on the error rate of SVM by the proposed FVS method, ...
This paper proposes a new method to reduce the number of support vectors so that speed up SVM decision. The method first obtains all the support vectors by ...
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Abstract. In this paper, we proposed a method to speed up the test phase of. SVM based on Feature Vector Selection method (FVS). In the method, the.
Jul 19, 2018 · Now there are a few ways to speed up the non-linear kernel SVMs: Use the SGDClassifier instead and provide proper parameters for loss, penalty ...
Abstract—In BCI research community, support vector machine (SVM) is an effective method for motor imagery (MI)- based electroencephalographic (EEG) ...
The method for improving the speed (the "reduced set" method) does so by approximating the support vector decision sur- face. We apply this method to achieve a ...
In this paper several methods for speeding up the running time of support vector machines (SVMs) are compared in terms of the speed-up factor and the.
We apply this method to achieve a factor of fifty speedup in test phase over the virtual support vector machine. The combined approach yields a machine which is ...