A hyperparameters selection technique for support vector regression models.
Panagiotis TsirikoglouSimon AbrahamFrancesco ContinoChris LacorGhader GhorbaniaslPublished in: Appl. Soft Comput. (2017)
Keyphrases
- hyperparameters
- regression model
- model selection
- support vector
- cross validation
- gaussian process
- posterior distribution
- support vector regression
- sample size
- gaussian processes
- regression methods
- machine learning
- bayesian framework
- prediction model
- bayesian inference
- closed form
- parameter estimation
- ls svm
- regression problems
- decision function
- em algorithm
- noise level
- feature selection
- random sampling
- learning machines
- maximum a posteriori
- incomplete data
- logistic regression
- maximum likelihood
- variable selection
- error rate
- feature vectors
- missing values
- approximate inference
- kernel function
- support vector machine
- training data
- genetic algorithm