CatBoost: Unbiased Boosting with Categorical Features, Liudmila Prokhorenkova, Gleb Gusev, Aleksandr Vorobev, Anna Veronika Dorogush, Andrey Gulin, 2018Advances in Neural Information Processing Systems, Vol. 31 (NeurIPS) - This foundational paper introduces the CatBoost algorithm, detailing its unique components, including Oblivious Trees, and elaborates on their structure and advantages.
CatBoost Documentation: CatBoost Tree Structure, Yandex, 2023 (Yandex) - The official documentation provides an authoritative explanation of CatBoost's tree structure, offering insights into the design rationale and practical implications of Oblivious Trees.
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, Aurélien Géron, 2022 (O'Reilly Media) - This widely recognized book offers a comprehensive foundation in decision trees, ensemble methods, and gradient boosting, helping readers understand the general context for CatBoost's tree design choices.