Selecting locally specialised classifiers for one-class classification ensembles.
Bartosz KrawczykBoguslaw CyganekPublished in: Pattern Anal. Appl. (2017)
Keyphrases
- imbalanced data
- ensemble learning
- decision trees
- classifier ensemble
- weighted voting
- combining classifiers
- multiple classifier systems
- diversity measures
- ensemble classifier
- test set
- binary classifiers
- ensemble methods
- machine learning algorithms
- naive bayes
- training set
- decision stumps
- supervised classification
- classifier combination
- trained classifiers
- majority voting
- feature ranking
- single class
- decision boundary
- novelty detection
- training data
- support vector
- multiple classifiers
- binary classification
- feature selection
- fusion methods
- base classifiers
- training samples
- density estimation
- machine learning
- ensemble members
- multi class
- training examples
- classification algorithm
- linear classifiers
- classification models
- selection algorithm
- random forests
- classification systems