How to tune the RBF SVM hyperparameters? An empirical evaluation of 18 search algorithms.
Jacques WainerPablo FonsecaPublished in: Artif. Intell. Rev. (2021)
Keyphrases
- hyperparameters
- support vector
- search algorithm
- radial basis function
- support vector machine svm
- cross validation
- gaussian process
- support vector machine
- ls svm
- gaussian processes
- grid search
- model selection
- decision function
- regularization parameter
- kernel function
- svm classifier
- rbf neural network
- feature selection
- random sampling
- closed form
- kernel parameters
- bayesian inference
- incremental learning
- em algorithm
- search space
- bayesian framework
- noise level
- sample size
- maximum likelihood
- artificial neural networks
- decision trees
- parameter settings
- support vector regression
- upper bound
- knn
- training data