Learning from Imbalanced Data Streams Based on Over-Sampling and Instance Selection.
Ireneusz CzarnowskiPublished in: ICCS (3) (2021)
Keyphrases
- instance selection
- learning from imbalanced data
- imbalanced data
- imbalanced datasets
- sampling methods
- feature selection
- support vector machine
- nearest neighbor
- text classification
- data reduction
- classification accuracy
- random forest
- multiple instance learning
- concept drift
- multi class
- supervised learning
- semi supervised learning
- data streams
- random sampling
- class distribution
- knowledge discovery and data mining
- linear regression
- machine learning
- sampling algorithm
- class imbalance
- classification algorithm
- unlabeled data
- k nearest neighbor
- pairwise
- decision trees
- neural network