SETL: a transfer learning based dynamic ensemble classifier for concept drift detection in streaming data.
Shruti AroraRinkle RaniNitin SaxenaPublished in: Clust. Comput. (2024)
Keyphrases
- concept drift
- drift detection
- streaming data
- transfer learning
- ensemble classifier
- data streams
- concept drifting data streams
- learning tasks
- ensemble learning
- non stationary
- classification algorithm
- knowledge transfer
- data distribution
- change detection
- reinforcement learning
- active learning
- labeled data
- machine learning
- stream data
- semi supervised learning
- multi task
- collaborative filtering
- text categorization
- incoming data
- text classification
- unlabeled data
- multi task learning
- neural network
- feature selection
- supervised learning
- learning algorithm
- machine learning algorithms