Handling imbalanced data sets with synthetic boundary data generation using bootstrap re-sampling and AdaBoost techniques.
Putthiporn ThanathamatheeChidchanok LursinsapPublished in: Pattern Recognit. Lett. (2013)
Keyphrases
- data generation
- imbalanced data sets
- active learning
- random sampling
- multi class
- imbalanced data
- streaming data
- sample size
- learning algorithm
- data streams
- high throughput
- decision trees
- co training
- support vector
- monte carlo
- change detection
- ensemble methods
- feature extraction
- sampling methods
- feature selection
- sliding window
- training data
- sampling algorithm
- minority class
- data mining