In-Sample and Out-of-Sample Model Selection and Error Estimation for Support Vector Machines.
Davide AnguitaAlessandro GhioLuca OnetoSandro RidellaPublished in: IEEE Trans. Neural Networks Learn. Syst. (2012)
Keyphrases
- error estimation
- model selection
- learning machines
- sample size
- cross validation
- error estimates
- support vector
- hyperparameters
- generalization error
- bayesian learning
- feature selection
- parameter estimation
- mixture model
- regression model
- machine learning
- vc dimension
- variable selection
- marginal likelihood
- model selection criteria
- selection criterion
- automatic model selection
- leave one out cross validation
- generalization bounds
- statistical inference
- logistic regression
- kernel function
- kernel machines
- bayesian methods
- classification accuracy
- bayesian information criterion
- gaussian process
- information criterion
- random sampling
- bayesian framework
- closed form