Boosting RVM Classifiers for Large Data Sets.
Catarina SilvaBernardete RibeiroAndrew H. SungPublished in: ICANNGA (2) (2007)
Keyphrases
- ensemble learning
- relevance vector machine
- randomized trees
- weak classifiers
- weak learners
- boosting algorithms
- feature selection
- improving classification accuracy
- boosting framework
- ensemble classifier
- learning machines
- data sets
- majority voting
- support vector machine
- relevance vector machines
- accurate classifiers
- support vector
- decision trees
- decision stumps
- strong classifier
- multiple classifier systems
- training data
- loss function
- naive bayes
- linear classifiers
- multiclass classification
- multi class
- svm classifier
- adaboost algorithm
- weighted voting
- ensemble methods
- bayesian classifiers
- boosted classifiers
- machine learning
- classification algorithm
- machine learning algorithms
- combining classifiers
- generalization ability
- gaussian processes
- learning algorithm
- classification models
- discriminative classifiers
- feature set
- training set
- training examples
- base classifiers
- classifier combination
- classifier ensemble
- feature extraction
- bayesian learning
- combining multiple
- binary classifiers