What Techniques Can Be Used to Address Class Imbalance?
Several techniques can be implemented to handle class imbalance:
Resampling Methods: Techniques like oversampling the minority class or undersampling the majority class can balance the dataset. Algorithmic Solutions: Some algorithms are designed to handle class imbalance better, such as cost-sensitive learning and anomaly detection. Ensemble Techniques: Methods like Random Forest and Boosting can help mitigate the effects of class imbalance.
