CatBoost Reviews and details

Social recommendations and mentions

• What's New with AWS: Amazon SageMaker built-in algorithms now provides four new Tabular Data Modeling Algorithms

  CatBoost is another popular and high-performance open-source implementation of the Gradient Boosting Decision Tree (GBDT). To learn how to use this algorithm, please see example notebooks for Classification and Regression. - Source: dev.to / almost 2 years ago

• Writing the fastest GBDT libary in Rust

  Here are our benchmarks on training time comparing Tangram's Gradient Boosted Decision Tree Library to LightGBM, XGBoost, CatBoost, and sklearn. - Source: dev.to / over 2 years ago

• Data Science toolset summary from 2021

  Catboost - CatBoost is an open-source software library developed by Yandex. It provides a gradient boosting framework which attempts to solve for Categorical features using a permutation driven alternative compared to the classical algorithm. Link - https://catboost.ai/. - Source: dev.to / over 2 years ago

• CatBoost Quickstart — ML Classification

  CatBoost is an open source algorithm based on gradient boosted decision trees. It supports numerical, categorical and text features. Check out the docs. - Source: dev.to / about 3 years ago