Kernel PLS Regression II: Kernel Partial Least Squares Regression by Projecting Both Independent and Dependent Variables into Reproducing Kernel Hilbert Space.
Yan PeiPublished in: SMC (2018)
Keyphrases
- partial least squares regression
- reproducing kernel hilbert space
- kernel methods
- loss function
- kernel function
- euclidean space
- domain adaptation
- density estimation
- distance measure
- special case
- learning theory
- real valued
- data dependent
- gaussian process
- neural network
- pairwise
- kernel matrix
- independent variables
- dependent variables
- learning problems
- support vector machine
- support vector
- input space
- learning tasks
- regression analysis
- feature selection
- data mining