Combining Bagging, Boosting and Dagging for Classification Problems.
Sotiris B. KotsiantisDimitris KanellopoulosPublished in: KES (2) (2007)
Keyphrases
- ensemble methods
- ensemble learning
- base classifiers
- ensemble classification
- randomized trees
- gradient boosting
- weak classifiers
- machine learning
- random forests
- decision tree ensembles
- combining multiple
- variance reduction
- ensemble classifier
- random forest
- decision trees
- learning algorithm
- decision stumps
- generalization ability
- loss function
- feature selection
- multi class
- majority voting
- weak learners
- multiple classifier systems
- prediction accuracy
- class distribution
- ensemble members
- benchmark datasets
- machine learning methods
- imbalanced data
- subspace methods
- base learners
- rotation forest