Tag Archives: SVM

Empirical Evaluation of Resampling Procedures for Optimising SVM Hyperparameters

Tuning the regularisation and kernel hyperparameters is a vital step in optimising the generalisation performance of kernel methods, such as the support vector machine (SVM). This is most often performed by minimising a resampling/cross-validation based model selection criterion, however there … Continue reading

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Empirical comparison of cross-validation and internal metrics for tuning SVM hyperparameters

Hyperparameter tuning is a mandatory step for building a support vector machine classifier. In this article, the authors study some methods based on metrics of the training set itself, and not the performance of the classifier on a different test … Continue reading

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