Combining Answers of Sub-classifiers in the Bagging-Feature Ensembles.
Jerzy StefanowskiPublished in: RSEISP (2007)
Keyphrases
- ensemble learning
- ensemble methods
- decision trees
- ensemble classifier
- combining classifiers
- imbalanced data
- classifier ensemble
- base classifiers
- rotation forest
- majority voting
- ensemble members
- random forest
- multiple classifier systems
- individual classifiers
- feature set
- weighted voting
- decision stumps
- feature ranking
- ensemble classification
- ensemble selection
- feature subset
- meta learning
- random forests
- randomized trees
- naive bayes
- weak classifiers
- multiple classifiers
- voting methods
- random subspace
- feature vectors
- base learners
- neural network ensembles
- training set
- multi class
- feature selection
- machine learning algorithms
- decision tree classifiers
- subspace methods
- diversity measures
- benchmark datasets
- learning machines
- machine learning methods
- generalization ability
- class distribution
- combining multiple
- classifier combination
- training data
- class label noise
- accurate classifiers
- single feature
- feature values
- multiple features
- training samples