Pages that link to "Item:Q1669630"
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The following pages link to Tuning of the hyperparameters for \(L2\)-loss SVMs with the RBF kernel by the maximum-margin principle and the jackknife technique (Q1669630):
Displaying 3 items.
- Tuning kernel parameters for SVM based on expected square distance ratio (Q2282123) (← links)
- Hyper-parameter optimization for support vector machines using stochastic gradient descent and dual coordinate descent (Q2308188) (← links)
- Choosing shape parameters for regression in reproducing kernel Hilbert space and variable selection (Q6050675) (← links)
