How large should ensembles of classifiers be?
Daniel Hernández-LobatoGonzalo Martínez-MuñozAlberto SuárezPublished in: Pattern Recognit. (2013)
Keyphrases
- decision trees
- ensemble learning
- ensemble classifier
- classifier ensemble
- weighted voting
- multiple classifier systems
- diversity measures
- imbalanced data
- combining classifiers
- training data
- ensemble methods
- machine learning algorithms
- support vector
- trained classifiers
- feature set
- linear classifiers
- feature ranking
- base learners
- supervised classification
- classification algorithm
- individual classifiers
- learning algorithm
- naive bayes
- classifier fusion
- svm classifier
- multiple classifiers
- random forests
- majority voting
- classifier combination
- random forest
- classification systems
- decision stumps
- ensemble members
- meta learning
- base classifiers
- training examples
- support vector machine svm
- data sets