Kernel PLS variants for regression.
Luc HoegaertsJohan A. K. SuykensJoos VandewalleBart De MoorPublished in: ESANN (2003)
Keyphrases
- partial least squares
- principal component regression
- partial least squares regression
- regression method
- kernel ridge regression
- regression model
- kernel regression
- sparse kernel
- regression methods
- reproducing kernel hilbert space
- kernel space
- discriminant analysis
- dimension reduction
- multiple regression
- gaussian processes
- classification and regression problems
- kernel function
- gaussian process regression
- support vector
- principal components
- kernel partial least squares
- canonical correlation analysis
- kernel methods
- regression algorithm
- feature space
- model selection
- principal component analysis
- partial least square regression
- neural network
- high dimensional
- linear regression
- support vector regression
- sparse regression
- dimensionality reduction
- locally weighted
- hilbert schmidt independence criterion
- regression problems