How does early stopping work in Decision Trees?

Early stopping prevents further splitting when certain conditions like depth or sample size thresholds are met.

Early stopping is a form of pre-pruning that halts tree growth based on constraints such as max_depth, min_samples_split, min_samples_leaf, or minimum impurity decrease. It reduces overfitting by preventing overly complex trees. However, it can introduce bias if stopping criteria are too strict. It is computationally efficient compared to post-pruning.