On the VC Dimension of Bounded Margin Classifiers.
Don R. HushClint ScovelPublished in: Mach. Learn. (2001)
Keyphrases
- vc dimension
- risk bounds
- generalization bounds
- support vector
- upper bound
- learning machines
- sample complexity
- concept classes
- inductive inference
- empirical risk minimization
- half spaces
- sample size
- lower bound
- decision boundary
- training set
- minimum margin
- statistical learning theory
- generalization error
- linear classifiers
- uniform convergence
- pac learning
- training data
- decision trees
- boosting algorithms
- concept class
- feature selection
- worst case
- data dependent
- compression scheme
- feature set
- learning algorithm
- supervised classification
- support vector machine
- training samples
- svm classifier
- euclidean space
- theoretical analysis
- model selection
- machine learning algorithms
- supervised learning
- function classes
- feature vectors
- objective function