A new training set-based regularization for regression techniques.
Youness NajiLaurent Le BrusquetGilles FleuryPublished in: EUSIPCO (2004)
Keyphrases
- training set
- kernel ridge regression
- reproducing kernel hilbert space
- test set
- cross validation
- regression model
- training data
- supervised learning
- classification accuracy
- test data
- nearest neighbor
- active learning
- model selection
- regularization parameter
- input space
- data sets
- parameter selection
- regression problems
- gradient boosting
- training examples
- kernel methods
- prior information
- regression algorithm
- feature space
- decision trees
- simple linear
- support vector
- face images
- linear regression
- training samples
- active appearance models
- data dependent
- empirical risk minimization
- training patterns
- ridge regression
- error rate
- class labels
- unlabeled data
- positive and negative examples
- regression methods
- support vector machine
- support vector regression
- partial least squares
- svm classifier
- classification algorithm
- gaussian processes
- generalization error