Kernel ridge regression for out-of-sample mapping in supervised manifold learning.
Carlotta OrsenigoCarlo VercellisPublished in: Expert Syst. Appl. (2012)
Keyphrases
- manifold learning
- kernel ridge regression
- semi supervised
- low dimensional
- parameter selection
- gradient boosting
- dimensionality reduction
- kernel methods
- dimension reduction
- feature extraction
- high dimensional
- supervised learning
- unsupervised learning
- semi supervised learning
- labeled data
- high dimensional data
- subspace learning
- sparse representation
- learning algorithm
- feature space
- loss function
- high dimensionality