Cluster-based ensemble of classifiers.
Ashfaqur RahmanBrijesh K. VermaPublished in: Expert Syst. J. Knowl. Eng. (2013)
Keyphrases
- ensemble learning
- ensemble classifier
- classifier ensemble
- multiple classifiers
- training data
- ensemble pruning
- majority voting
- training set
- individual classifiers
- ensemble methods
- randomized trees
- majority vote
- decision tree classifiers
- final classification
- decision trees
- accurate classifiers
- weighted voting
- diversity measures
- combining classifiers
- classifier combination
- feature selection
- multiple classifier systems
- random forests
- ensemble classification
- trained classifiers
- one class support vector machines
- binary classification problems
- neural network
- class label noise
- linear support vector machines
- ensemble members
- imbalanced data
- mining concept drifting data streams
- feature set
- classification systems
- naive bayes
- random forest
- class labels
- support vector
- publicly available data sets
- learning algorithm
- linear classifiers
- base classifiers
- pruning method
- test set
- machine learning methods
- machine learning algorithms
- classification algorithm
- classifier fusion
- concept drifting data streams
- weak learners
- machine learning
- rule induction algorithm
- support vector machine
- feature ranking
- text classification
- training examples
- prediction accuracy
- logistic regression
- combining multiple
- fusion methods
- base learners