What is the impact of imbalanced data on model performance curves?

What is the impact of imbalanced data on model performance curves?

Imbalanced data can lead to skewed performance curves, affecting metrics like precision and recall.

Can you explain how it affects precision and recall specifically?

Certainly! In imbalanced datasets, a model may achieve high accuracy by predicting the majority class, but this can result in low precision and recall for the minority class.

What techniques can be used to handle imbalanced data?

Common techniques include resampling methods like oversampling the minority class, undersampling the majority class, and using algorithms that are robust to class imbalance.

How do these techniques influence the performance curves?

These techniques can help improve the balance between precision and recall, leading to more informative performance curves that better reflect the model's ability to predict both classes.