--- id: xgboost version: "3.4.0" license: Apache-2.0 license_treatment: permissive maintenance: active --- # xgboost — XGBoost Python Package License: permissive · Maintenance: active · Popularity: top 1,000 on PyPI ## Install pip install xgboost uv add xgboost poetry add xgboost ## Description eXtreme Gradient Boosting =========== [![XGBoost-CI](https://github.com/dmlc/xgboost/workflows/XGBoost%20CI/badge.svg?branch=master)](https://github.com/dmlc/xgboost/actions) [![Documentation Status](https://readthedocs.org/projects/xgboost/badge/?version=latest)](https://xgboost.readthedocs.io) [![GitHub license](https://dmlc.github.io/img/apache2.svg)](./LICENSE) [![CRAN Status Badge](https://www.r-pkg.org/badges/version/xgboost)](https://cran.r-project.org/web/packages/xgboost) [![PyPI version](https://badge.fury.io/py/xgboost.svg)](https://pypi.python.org/pypi/xgboost/) [![Conda version](https://img.shields.io/conda/vn/conda-forge/py-xgboost.svg)](https://anaconda.org/conda-forge/py-xgboost) [![Optuna](https://img.shields.io/badge/Optuna-integrated-blue)](https://optuna.org) [![Twitter](https://img.shields.io/badge/@XGBoostProject--_.svg?style=social&logo=twitter)](https://twitter.com/XGBoostProject) [![OpenSSF Scorecard](https://api.securityscorecards.dev/projects/github.com/dmlc/xgboost/badge)](https://api.securityscorecards.dev/projects/github.com/dmlc/xgboost) [![Open In... ## AI interpretation — verify before relying XGBoost is a distributed gradient boosting library that trains tree-based machine learning models for classification, regression, and ranking tasks with high efficiency across single and distributed computing environments. Verdict: XGBoost 3.4.0 is a production-stable, actively maintained gradient boosting framework with no known vulnerabilities and permissive Apache-2.0 licensing. Medium install friction is typical for compiled ML libraries; GPU acceleration is optional via nvidia-nccl-cu13. [View on SkillFed](https://skillfed.io/packages/xgboost) · [View on PyPI](https://pypi.org/project/xgboost/)