Sharp error bounds for imbalanced classification: how many examples in the minority class?
Anass AghbalouAnne SabourinFrançois PortierPublished in: AISTATS (2024)
Keyphrases
- error bounds
- minority class
- class imbalance
- imbalanced data sets
- imbalanced datasets
- majority class
- imbalanced data
- class distribution
- cost sensitive learning
- decision boundary
- class imbalanced
- imbalanced data classification
- classification error
- support vector machine
- highly skewed
- high dimensionality
- theoretical analysis
- cost sensitive
- rare events
- nearest neighbour
- class labels
- sampling methods
- machine learning
- training samples
- feature selection
- single class
- training set
- active learning
- training dataset
- binary classification
- feature selection algorithms
- worst case
- training examples
- classification accuracy
- supervised learning
- misclassification costs
- probability estimation
- imbalanced class distribution
- machine learning methods
- training data
- feature extraction
- classification models
- decision trees
- pattern classification