What is class imbalance in segmentation?

What is class imbalance in segmentation?

Class imbalance in segmentation refers to a situation where certain classes of data are underrepresented compared to others, leading to biased model performance.

Why is class imbalance a problem in machine learning?

It can lead to models that are biased towards the majority class, resulting in poor performance on minority classes, which is critical in applications like medical imaging.

How can I handle class imbalance in my dataset?

You can use techniques like resampling (oversampling the minority class or undersampling the majority class), using different evaluation metrics, or applying algorithms that are robust to class imbalance.

What are some common metrics to evaluate models with class imbalance?

Common metrics include precision, recall, F1-score, and the area under the ROC curve (AUC-ROC), which provide better insights than accuracy alone.