Extensions to Online Feature Selection Using Bagging and Boosting.
Gregory DitzlerJoseph LaBarckJames RitchieGail RosenRobi PolikarPublished in: IEEE Trans. Neural Networks Learn. Syst. (2018)
Keyphrases
- feature selection
- ensemble learning
- ensemble classification
- ensemble methods
- ensemble classifier
- decision stumps
- machine learning
- base classifiers
- randomized trees
- meta learning
- decision trees
- text classification
- imbalanced data
- majority voting
- mutual information
- online learning
- text categorization
- gradient boosting
- batch mode
- feature selection algorithms
- learning algorithm
- multi class
- random forests
- prediction accuracy
- random forest
- select relevant features
- feature extraction
- support vector machine
- variance reduction
- dimensionality reduction
- feature set
- model selection
- selected features
- weak classifiers
- naive bayes
- feature subset
- discriminative features
- learning machines
- benchmark datasets
- classification accuracy
- support vector
- multi task
- decision tree ensembles