SVM hyperparameters tuning for recursive multi-step-ahead prediction.
Jie LiuEnrico ZioPublished in: Neural Comput. Appl. (2017)
Keyphrases
- hyperparameters
- support vector
- cross validation
- grid search
- model selection
- decision function
- ls svm
- gaussian process
- bayesian inference
- regularization parameter
- closed form
- random sampling
- support vector machine svm
- bayesian framework
- gaussian processes
- feature selection
- em algorithm
- prior information
- support vector machine
- maximum a posteriori
- generalization ability
- sample size
- parameter settings
- svm classifier
- noise level
- kernel function
- random forest
- parameter optimization
- training set
- maximum likelihood
- incomplete data
- parameter space
- feature space
- kernel parameters
- incremental learning
- knn
- high dimensional
- support vector regression
- data sets
- random search