catboost

name	catboost
description	CatBoost gradient boosting with categoricals. Use for tabular ML.

CatBoost

CatBoost (Yandex) is arguably the easiest boosting library to use because it handles Categorical Features automatically and perfectly without tuning.

When to Use

• Categorical Data: If you have many strings/IDs, CatBoost is king.
• Default Params: Works incredibly well out of the box.

Core Concepts

Ordered Boosting

A technique to avoid target leakage (overfitting) during training.

Symmetric Trees

Builds balanced trees, which are faster at inference time.

Best Practices (2025)

Do:

• Use pool: Pool() is efficient for data loading.
• Use GPU: CatBoost's GPU implementation is highly optimized.

Don't:

• Don't One-Hot Encode: Let CatBoost handle it natively.

References

• CatBoost Documentation