What is CatBoost and why is it unique among boosting algorithms?

CatBoost is a gradient boosting algorithm that handles categorical features natively and reduces prediction shift.

CatBoost introduces ordered boosting, which prevents target leakage by using permutation-based training. It also handles categorical variables natively using target statistics instead of requiring preprocessing. This reduces overfitting and improves performance on datasets with many categorical features.