CatBoost
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About
CatBoost is a high-performance, open-source library for gradient boosting on decision trees. Developed by Yandex, it's used in various applications like search, recommendation systems, and self-driving cars. It offers features like categorical feature support, fast GPU implementation, improved accuracy, and fast prediction. CatBoost stands out by providing great results with default parameters, reducing the need for extensive parameter tuning. It supports training on CPU/GPU clusters and can handle large datasets.
Platform
Task
Features
• great quality without parameter tuning
• fast and scalable gpu version
• improved accuracy
• fast prediction
• categorical features support
Pricing Plans
Free
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