Yandex Catboost: Open-source Gradient Boosting Library

CatBoost is a state-of-the-art gradient boosting algorithm that trains a series of predictive models to achieve best-in-class accuracy. Developed by Yandex researchers and engineers, it is the successor to the MatrixNet algorithm that is widely used within the company for ranking, weather forecasting and making recommendations. CatBoost is an out-of-the box solution to a variety of problems across a wide range of industries.