Catboost stands out for its efficient handling of categorical data, utilizing techniques like one hot encoding and target encoding to streamline preprocessing. With features such as ordered boosting and symmetric decision trees, it offers faster training times and reduced risk of overfitting. This makes Catboost an excellent choice for various tasks, particularly when working with tabular data.
