What is gradient clipping in boosting ensembles?

Gradient clipping limits extreme gradient values to stabilize boosting training.

In gradient boosting, large gradients from outliers can destabilize training and lead to overfitting. Gradient clipping restricts gradient values within a threshold range, improving numerical stability and generalization. This is especially important in deep boosting implementations and noisy datasets.