Rarity updated ensemble with oversampling: An ensemble approach to classification of imbalanced data streams.
Zahra NouriVahid KianiHamid FadisheiPublished in: Stat. Anal. Data Min. (2024)
Keyphrases
- class imbalance
- data streams
- imbalanced data
- binary classification problems
- classification accuracy
- concept drifting data streams
- concept drift
- decision trees
- final classification
- training set
- feature selection
- pattern recognition
- classification algorithm
- ensemble classifier
- classifier ensemble
- pattern classification
- support vector
- classification models
- sliding window
- class labels
- ensemble learning
- model selection
- minority class
- class distribution
- imbalanced datasets
- random forest
- cost sensitive
- training samples
- feature space
- machine learning
- multiple classifiers
- majority voting
- wrapper feature selection
- data stream classification
- data sets
- cost sensitive learning
- streaming data
- random forests
- ensemble methods
- benchmark datasets
- support vector machine svm
- text classification
- feature vectors
- feature extraction
- neural network