Bias and Variance Optimization for SVMs Model Selection.
Alejandro Rosales-PérezHugo Jair EscalanteJesus A. GonzalezCarlos A. Reyes GarcíaPublished in: FLAIRS Conference (2013)
Keyphrases
- model selection
- cross validation
- selection criterion
- feature selection
- support vector
- hyperparameters
- parameter estimation
- machine learning
- error estimation
- bayesian learning
- sample size
- learning machines
- mixture model
- regression model
- low variance
- statistical learning
- generalization error
- statistical inference
- variable selection
- kernel machines
- grid search
- hypothesis tests
- model selection criteria
- automatic model selection
- bayesian methods
- information criterion
- parameter determination
- support vector machine svm
- statistical learning theory
- multi class
- support vector machine
- upper bound
- learning algorithm
- feature selection algorithms
- feature space
- training set
- marginal likelihood
- bayesian information criterion
- least squares
- kernel function
- kernel methods
- learning problems