The effects of classifiers diversity on the accuracy of stacking.
Mariele LanesEduardo N. BorgesRenata GalantePublished in: SEKE (2017)
Keyphrases
- high accuracy
- individual classifiers
- classifier ensemble
- fold cross validation
- combining classifiers
- training data
- support vector
- diversity measures
- ensemble learning
- training set
- roc curve
- decision trees
- class labels
- prediction accuracy
- confusion matrix
- feature selection
- highest accuracy
- roc analysis
- confusion matrices
- multiple classifier systems
- supervised classification
- multiple classifiers
- combining multiple
- classification method
- feature set
- computational cost
- ensemble pruning
- feature extraction