Catboost
A comprehensive skill catalog for AI agents
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CatBoost gradient boosting with categoricals. Use for tabular ML.
SKILL.md
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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.