Optimal selection of ensemble classifiers using measures of competence and diversity of base classifiers.
Rafal LysiakMarek KurzynskiTomasz WoloszynskiPublished in: Neurocomputing (2014)
Keyphrases
- ensemble classifier
- base classifiers
- optimal selection
- diversity measures
- classifier ensemble
- ensemble methods
- multi class
- decision trees
- ensemble learning
- training set
- random forest
- majority voting
- classification error
- test data
- naive bayes
- classification models
- training samples
- class labels
- cost sensitive
- rotation forest
- concept drift
- prediction accuracy
- feature selection
- feature set
- training data
- non stationary
- text classification
- text mining
- small number
- support vector machine
- active learning
- feature vectors
- image processing