focal loss

Focal loss is a loss function that is used in deep learning models for addressing the problem of imbalanced datasets. It assigns higher weights to the minority class samples, focusing more on difficult-to-classify examples during the training process. This helps to mitigate the impact of the majority class dominating the loss computation and enhances the model's ability to handle imbalanced data.

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