Ambiguity-guided dynamic selection of ensemble of classifiers.
Eulanda Miranda dos SantosRobert SabourinPatrick MaupinPublished in: FUSION (2007)
Keyphrases
- ensemble learning
- classifier ensemble
- ensemble classifier
- ensemble pruning
- multiple classifiers
- training data
- majority voting
- training set
- combining classifiers
- ensemble methods
- class label noise
- individual classifiers
- randomized trees
- decision trees
- multiple classifier systems
- accurate classifiers
- majority vote
- feature selection
- final classification
- weak learners
- decision tree classifiers
- weak classifiers
- mining concept drifting data streams
- pruning method
- linear support vector machines
- feature ranking
- support vector
- diversity measures
- machine learning algorithms
- classification systems
- random forest
- feature set
- publicly available data sets
- learning algorithm
- weighted voting
- rule induction algorithm
- naive bayes
- classifier combination
- training samples
- test set
- base classifiers
- ensemble members
- concept drifting data streams
- neural network
- svm classifier
- ensemble classification
- pruning algorithm
- linear classifiers
- machine learning
- knn
- machine learning methods
- combining multiple
- logistic regression
- binary classification problems
- bias variance decomposition
- imbalanced data
- classifier fusion
- data sets