Kernel methods for regression model based on variable selection.
Seiichi IkedaYoshiharu SatoPublished in: Int. J. Knowl. Eng. Soft Data Paradigms (2009)
Keyphrases
- variable selection
- kernel methods
- kernel ridge regression
- reproducing kernel hilbert space
- support vector
- model selection
- linear models
- cross validation
- kernel function
- input variables
- high dimensional
- machine learning
- learning problems
- regression problems
- support vector machine
- feature space
- regression model
- kernel matrices
- kernel matrix
- dimension reduction
- learning tasks
- high dimensional data
- support vector regression
- ls svm
- input space
- linear regression
- feature selection
- data mining
- kernel learning
- training set
- multiple kernel learning
- pattern recognition
- gaussian processes
- principal component analysis
- pairwise
- nearest neighbor