Ensemble of Classifiers Based on Hard Instances.
Isis BonetAbdel RodríguezRicardo Grau ÁbaloMaría M. GarcíaPublished in: MCPR (2011)
Keyphrases
- training instances
- trained classifiers
- classifier ensemble
- ensemble learning
- multiple classifiers
- ensemble classifier
- training data
- ensemble pruning
- training set
- combining classifiers
- final classification
- majority voting
- data stream classification
- ensemble methods
- majority vote
- ensemble classification
- weighted voting
- individual classifiers
- multiple classifier systems
- instance selection
- weak learners
- accurate classifiers
- decision tree classifiers
- class label noise
- neural network
- classifier combination
- imbalanced data
- concept drifting data streams
- weak classifiers
- random forests
- ensemble members
- randomized trees
- support vector
- svm classifier
- feature selection
- random instances
- diversity measures
- collective classification
- linear classifiers
- decision trees
- base classifiers
- support vector machine
- bias variance decomposition
- learning algorithm
- training samples
- one class support vector machines
- rule induction algorithm
- mining concept drifting data streams
- multiple instance learning
- classification algorithm
- random forest
- active learning
- classification accuracy
- feature set
- machine learning algorithms
- phase transition
- classification models
- minority class
- concept drift
- test instances
- roc curve
- combining multiple