Maximal-discrepancy bounds for regularized classifiers.
Sergio DecherchiPaolo GastaldoJudith RediRodolfo ZuninoPublished in: IJCNN (2009)
Keyphrases
- pac bayes
- decision trees
- generalization error bounds
- training set
- lower bound
- multiple classifiers
- risk bounds
- linear classifiers
- upper bound
- support vector
- naive bayes
- least squares
- test set
- generalization bounds
- training data
- convex combinations
- classifier ensemble
- classification rate
- kernel classifiers
- error bounds
- classification algorithm
- machine learning algorithms
- objective function
- classifier combination
- feature selection
- binary classifiers
- learning machines
- supervised classification
- ensemble learning
- classification models
- feature subset
- learning problems
- class labels
- training samples