An iterative boosting-based ensemble for streaming data classification.
João Roberto Bertini JuniorMaria do Carmo NicolettiPublished in: Inf. Fusion (2019)
Keyphrases
- streaming data
- concept drifting data streams
- concept drift
- ensemble classification
- ensemble classifier
- ensemble methods
- data streams
- weak learners
- ensemble learning
- majority voting
- decision trees
- feature selection
- classifier ensemble
- classification accuracy
- drift detection
- sliding window
- data distribution
- multiple classifier systems
- generalization ability
- base learners
- learning algorithm
- benchmark datasets
- feature space
- feature vectors
- machine learning
- base classifiers
- inductive learning algorithms
- feature extraction
- evolving data streams
- data stream mining
- training set
- supervised learning
- text classification
- anomaly detection
- multi class
- high dimensional
- weak classifiers
- prediction accuracy
- machine learning methods