A New Ensemble Learning Algorithm using Regional Classifiers.
Byungwoo LeeSungha ChoiByonghwa OhJihoon YangSungyong ParkPublished in: Int. J. Artif. Intell. Tools (2013)
Keyphrases
- learning algorithm
- training data
- machine learning algorithms
- ensemble learning
- accurate classifiers
- classifier ensemble
- training examples
- multiple classifiers
- ensemble classifier
- generalization ability
- ensemble pruning
- classification algorithm
- training set
- base learners
- training samples
- ensemble methods
- machine learning
- majority voting
- decision trees
- decision stumps
- majority vote
- individual classifiers
- random forests
- feature selection
- active learning
- weak learners
- machine learning methods
- ensemble classification
- base classifiers
- ensemble members
- multiple classifier systems
- randomized trees
- classification accuracy
- weighted voting
- data sets
- combining classifiers
- concept drifting data streams
- augmented naive bayes
- classifier combination
- class label noise
- co training
- support vector
- supervised learning
- naive bayes
- svm classifier
- random forest
- learning problems
- feature ranking
- trained classifiers
- class labels
- learning tasks
- final classification
- learning rate
- classification models
- generalization error
- pruning algorithm
- back propagation
- learning scheme
- binary classifiers
- rule induction algorithm
- semi supervised learning
- bias variance decomposition
- imbalanced data
- binary classification problems
- mining concept drifting data streams
- neural network