Stacking Strong Ensembles of Classifiers.
Stamatios-Aggelos N. AlexandropoulosChristos K. AridasSotiris B. KotsiantisMichael N. VrahatisPublished in: AIAI (2019)
Keyphrases
- ensemble learning
- combining classifiers
- base classifiers
- ensemble classifier
- decision trees
- multiple classifiers
- classifier combination
- ensemble methods
- diversity measures
- weighted voting
- naive bayes
- majority voting
- classifier ensemble
- individual classifiers
- training set
- combining multiple
- training data
- generalization ability
- learning machines
- support vector
- imbalanced data
- linear classifiers
- supervised classification
- multiple classifier systems
- data sets
- random forest
- classification algorithm
- classification systems
- decision boundary
- test set
- machine learning algorithms
- base learners
- feature ranking
- unlabeled data
- feature set
- feature selection
- word sense induction
- classifier fusion
- decision stumps
- ensemble members
- weak learners
- classification models
- feature subset
- logistic regression
- class labels
- training samples
- labeled data
- face recognition
- neural network