Description: CatBoost is an open-source gradient boosting on decision trees library with categorical features support out of the box, successor of the MatrixNet algorithm developed by Yandex.
CatBoost is a high-performance open source library for gradient boosting on decision trees
CatBoost is an algorithm for gradient boosting on decision trees . It is developed by Yandex researchers and engineers, and is used for search, recommendation systems, personal assistant, self-driving cars, weather prediction and many other tasks at Yandex and in other companies, including CERN, Cloudflare, Careem taxi. It is in open-source and can be used by anyone.