Variable Selection for the Prediction of C[0, 1]-Valued Autoregressive Processes using Reproducing Kernel Hilbert Spaces.
Beatriz Bueno-LarrazJohannes KlepschPublished in: Technometrics (2019)
Keyphrases
- variable selection
- autoregressive
- reproducing kernel hilbert space
- input variables
- non stationary
- cross validation
- high dimensional
- dimension reduction
- model selection
- random fields
- sar images
- kernel methods
- ls svm
- prediction model
- high dimensional data
- kernel function
- loss function
- information extraction
- computer vision
- gaussian process
- low dimensional
- decision trees