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Last update: 16/07/2026

catboost

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Latest version: 1.2.10 registry icon
Maintenance score
100
Safety score
100
Popularity score
100
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Security
  Vulnerabilities
Version Suggest Low Medium High Critical
1.2.10 0 0 0 0 0
1.2.9 0 0 0 0 0
1.2.8 0 0 0 0 0
1.2.7 0 0 0 0 0
1.2.6 0 0 0 0 0
1.2.5 0 0 0 0 0
1.2.3 0 0 0 0 0
1.2.2 0 0 0 0 0
1.2.1.1 0 0 0 0 0
1.2.1 0 0 0 0 0
1.2 0 0 0 0 0
1.1.1 0 0 0 0 0
1.1 0 0 0 0 0
1.0.6 0 0 0 0 0
1.0.5 0 0 0 0 0
1.0.4 0 0 0 0 0
1.0.3 0 0 0 0 0
1.0.2 0 0 0 0 0
1.0.1 0 0 0 0 0
1.0.0 0 0 0 0 0
0.26.1 0 0 0 0 0
0.26 0 0 0 0 0
0.25.1 0 0 0 0 0
0.25 0 0 0 0 0
0.24.4 0 0 0 0 0
0.24.3 0 0 0 0 0
0.24.2 0 0 0 0 0
0.24.1 0 0 0 0 0
0.24 0 0 0 0 0
0.23.2 0 0 0 0 0
0.23.1 0 0 0 0 0
0.23 0 0 0 0 0
0.22 0 0 0 0 0
0.21 0 0 0 0 0
0.20.2 0 0 0 0 0
0.20.1 0 0 0 0 0
0.20 0 0 0 0 0
0.19.1 0 0 0 0 0
0.18.1 0 0 0 0 0
0.18 0 0 0 0 0
0.17.5 0 0 0 0 0
0.17.4 0 0 0 0 0
0.17.3 0 0 0 0 0
0.17.2 0 0 0 0 0
0.17.1 0 0 0 0 0
0.17 0 0 0 0 0
0.16.5 0 0 0 0 0
0.16.4 0 0 0 0 0
0.16.3 0 0 0 0 0
0.16.2 0 0 0 0 0
0.16.1 0 0 0 0 0
0.16 0 0 0 0 0
0.15.2 0 0 0 0 0
0.15.1 0 0 0 0 0
0.15 0 0 0 0 0
0.14.2 0 0 0 0 0
0.14.1 0 0 0 0 0
0.14.0 0 0 0 0 0
0.13.1 0 0 0 0 0
0.13 0 0 0 0 0
0.12.2 0 0 0 0 0
0.12.1.1 0 0 0 0 0
0.12.1 0 0 0 0 0
0.11.1 0 0 0 0 0
0.11.0 0 0 0 0 0
0.10.3 0 0 0 0 0
0.10.2 0 0 0 0 0
0.9.1.1 0 0 0 0 0
0.9.1 0 0 0 0 0
0.9 0 0 0 0 0
0.8.1.1 0 0 0 0 0
0.8.1 0 0 0 0 0
0.8 0 0 0 0 0
0.7.2.3 0 0 0 0 0
0.7.2.2 0 0 0 0 0
0.7.2.1 0 0 0 0 0
0.7.2 0 0 0 0 0
0.7.1 0 0 0 0 0
0.7 0 0 0 0 0
0.6.3 0 0 0 0 0
0.6.2 0 0 0 0 0
0.6.1.1 0 0 0 0 0
0.6.1 0 0 0 0 0
0.2.5 0 0 0 0 0
0.2.4 0 0 0 0 0
0.2.2 0 0 0 0 0
0.2.1 0 0 0 0 0
0.2 0 0 0 0 0
0.1.1.9 0 0 0 0 0
0.1.1.8 0 0 0 0 0
0.1.1.7 0 0 0 0 0
0.1.1.6 0 0 0 0 0
0.1.1.5 0 0 0 0 0
0.1.1.3 0 0 0 0 0
0.1.1 0 0 0 0 0

Stability
Latest release:

1.2.10 - This version is safe to use because it has no known security vulnerabilities at this time. Find out if your coding project uses this component and get notified of any reported security vulnerabilities with Meterian-X Open Source Security Platform

Licensing

Maintain your licence declarations and avoid unwanted licences to protect your IP the way you intended.

Apache-2.0   -   Apache License 2.0

Not a wildcard

Not proprietary

OSI Compliant

Website | Documentation | Tutorials | Installation | Release Notes

GitHub license PyPI version Conda Version GitHub issues Telegram Twitter

CatBoost is a machine learning method based on gradient boosting over decision trees.

Main advantages of CatBoost:

Get Started and Documentation

All CatBoost documentation is available here.

Install CatBoost by following the guide for the

Next you may want to explore:

If you cannot open documentation in your browser try adding yastatic.net and yastat.net to the list of allowed domains in your Privacy Badger.

CatBoost models in production

If you want to evaluate CatBoost model in your application read model api documentation.

Questions and bug reports

Help to Make CatBoost Better

News

Latest news are published on twitter.

Reference Paper

Anna Veronika Dorogush, Andrey Gulin, Gleb Gusev, Nikita Kazeev, Liudmila Ostroumova Prokhorenkova, Aleksandr Vorobev "Fighting biases with dynamic boosting". arXiv:1706.09516, 2017.

Anna Veronika Dorogush, Vasily Ershov, Andrey Gulin "CatBoost: gradient boosting with categorical features support". Workshop on ML Systems at NIPS 2017.

License

© YANDEX LLC, 2017-2026. Licensed under the Apache License, Version 2.0. See LICENSE file for more details.