A Boundary-Information-Based Oversampling Approach to Improve Learning Performance for Imbalanced Datasets.
Der-Chiang LiQi-Shi ShiYao-San LinLiang-Sian LinPublished in: Entropy (2022)
Keyphrases
- boundary information
- imbalanced datasets
- class imbalance
- minority class
- class distribution
- image segmentation
- cost sensitive learning
- sampling methods
- region growing
- active learning
- cost sensitive
- imbalanced data
- region merging
- support vector machine
- object segmentation
- concept drift
- nearest neighbour
- high dimensionality
- decision boundary
- training dataset
- classification error
- data sets
- image regions
- training data
- random sampling
- ensemble methods
- misclassification costs
- test set
- expectation maximization
- semi supervised
- training set
- computer vision