A semi-supervised clustering-based classification model for classifying imbalanced data streams in the presence of scarcely labelled data.
Kiran BhowmickMeera NarvekarPublished in: Int. J. Bus. Intell. Data Min. (2022)
Keyphrases
- labelled data
- unlabelled data
- data streams
- concept drift
- semi supervised
- class imbalance
- class distribution
- sliding window
- streaming data
- co training
- data sets
- data distribution
- sensor networks
- stream data
- change detection
- training data
- semi supervised learning
- supervised and unsupervised learning
- hierarchical text classification
- classification algorithm
- non stationary
- unsupervised learning
- single view
- hierarchical classification
- labeled data
- active learning
- image analysis
- data mining