Performance of global-local hybrid ensemble versus boosting and bagging ensembles.
Dustin BaumgartnerGürsel SerpenPublished in: Int. J. Mach. Learn. Cybern. (2013)
Keyphrases
- ensemble methods
- ensemble learning
- base classifiers
- ensemble members
- base learners
- rotation forest
- random forests
- negative correlation learning
- ensemble classifier
- prediction accuracy
- random forest
- decision trees
- decision tree ensembles
- machine learning methods
- majority voting
- benchmark datasets
- ensemble classification
- classifier ensemble
- ensemble selection
- weak learners
- decision stumps
- imbalanced data
- multi class
- weighted voting
- random subspace
- multiple classifier systems
- generalization ability
- training set
- meta learning
- neural network ensemble
- feature selection
- error function
- unlabeled data
- machine learning
- neural network ensembles
- cost sensitive
- tree ensembles
- feature subset
- learning algorithm
- classifier combination
- boosting algorithms
- weak classifiers
- support vector machine