Importance of detecting rare events and edge cases in machine learning
Detecting rare events and edge cases is crucial in machine learning for several reasons:
- Decision-making in critical scenarios: Rare events often represent critical scenarios or anomalies that require immediate attention or special treatment. For instance, in medical diagnosis, rare diseases or extreme cases might need urgent intervention. Accurate detection of these events can lead to better decision-making and prevent adverse consequences.
- Unbalanced datasets: Many real-world datasets suffer from class imbalance, where one class (often the rare event) is significantly underrepresented compared to the other classes. This can lead to biased models that perform poorly on the minority class. Detecting rare events helps identify the need for special handling, such as using resampling techniques or employing appropriate evaluation metrics to ensure fair evaluation.
- Fraud detection: In fraud detection...
