{"data":{"slug":"dmlc-xgboost","name":"xgboost","tagline":"Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. 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Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow","homepage_url":"https://xgboost.readthedocs.io/","license":"Apache-2.0","open_issues":472,"watchers":883,"ai_summary":null,"readme_excerpt":"<img src=\"https://xgboost.ai/images/logo/xgboost-logo-trimmed.png\" width=200/> eXtreme Gradient Boosting\n===========\n\n\n\n\n\n\n\n\n\n\n\n\n[Community](https://xgboost.ai/community) |\n[Documentation](https://xgboost.readthedocs.org) |\n[Resources](demo/README.md) |\n[Contributors](CONTRIBUTORS.md) |\n[Release Notes](https://xgboost.readthedocs.io/en/latest/changes/index.html)\n\nXGBoost is an optimized distributed gradient boosting library designed to be highly ***efficient***, ***flexible*** and ***portable***.\nIt implements machine learning algorithms under the [Gradient Boosting](https://en.wikipedia.org/wiki/Gradient_boosting) framework.\nXGBoost provides a parallel tree boosting (also known as GBDT, GBM) that solve many data science problems in a fast and accurate way.\nThe same code runs on major distributed environment (Kubernetes, Hadoop, SGE, Dask, Spark, PySpark) and can solve problems beyond billions of examples.\n\nLicense\n-------\n© Contributors, 2021. Licensed under an [Apache-2](https://github.com/dmlc/xgboost/blob/master/LICENSE) license.\n\nContribute to XGBoost\n---------------------\nXGBoost has been developed and used by a group of active community members. Your help is very valuable to make the package better for everyone.\nCheckout the [Community Page](https://xgboost.ai/community).\n\nReference\n---------\n- Tianqi Chen and Carlos Guestrin. [XGBoost: A Scalable Tree Boosting System](https://arxiv.org/abs/1603.02754). In 22nd SIGKDD Conference on Knowledge Discovery and Data Mining, 2016\n- XGBoost originates from research project at University of Washington.\n\nSponsors\n--------\nBecome a sponsor and get a logo here. See details at [Sponsoring the XGBoost Project](https://xgboost.ai/sponsors). The funds are used to defray the cost of continuous integration and testing infrastructure (https://xgboost-ci.net).\n\n## Open Source Collective sponsors\n \n\n### Sponsors\n[[Become a sponsor](https://opencollective.com/xgboost#sponsor)]\n\n<a href=\"https://www.nvidia.com/en-us/\" target=\"_blank\"><img src=\"https://raw.githubusercontent.com/xgboost-ai/xgboost-ai.github.io/master/images/sponsors/nvidia.jpg\" alt=\"NVIDIA\" width=\"72\" height=\"72\"></a>\n<a href=\"https://www.comet.com/site/?utm_source=xgboost&utm_medium=github&utm_content=readme\" target=\"_blank\"><img src=\"https://cdn.comet.ml/img/notebook_logo.png\" height=\"72\"></a>\n<a href=\"https://opencollective.com/tomislav1\" target=\"_blank\"><img src=\"https://images.opencollective.com/tomislav1/avatar/256.png\" height=\"72\"></a>\n<a href=\"https://databento.com/?utm_source=xgboost&utm_medium=sponsor&utm_content=display\"><img src=\"https://raw.githubusercontent.com/xgboost-ai/xgboost-ai.github.io/refs/heads/master/images/sponsors/databento.png\" height=\"72\"></a>\n<a href=\"https://www.intel.com/\" target=\"_blank\"><img src=\"https://images.opencollective.com/intel-corporation/2fa85c1/logo/256.png\" width=\"72\" height=\"72\"></a>\n\n### Backers\n[[Become a backer](https://opencollective.com/xgboost#backer)]\n\n<a href=\"https://opencollective.com/xgboost#backers\" target=\"_blank\"><img src=\"https://opencollective.com/xgboost/backers.svg?width=890\"></a>","github_created_at":"2014-02-06T17:28:03+00:00","created_at":"2026-07-11T23:24:49.579832+00:00","updated_at":"2026-07-11T23:24:58.034355+00:00","categories":[{"slug":"computer-vision","name":"Computer Vision","url":"https://www.graphcanon.com/categories/computer-vision","markdown_url":"https://www.graphcanon.com/categories/computer-vision.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/computer-vision"}],"tags":[{"slug":"c","name":"c++"},{"slug":"distributed-systems","name":"distributed systems"},{"slug":"gbdt","name":"gbdt"},{"slug":"gbm","name":"gbm"},{"slug":"gbrt","name":"gbrt"},{"slug":"machine-learning","name":"machine-learning"},{"slug":"xgboost","name":"xgboost"}],"trust":{"provenance":{"is_fork":false,"github_id":16587283,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-07-11T23:24:50.816Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":1,"days_since_push":1,"last_release_at":"2026-06-17T20:56:43Z"},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T23:24:51.187Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-07-11T23:24:50.566Z"},"languages":{"value":["c++"],"source":"github.language","observed_at":"2026-07-11T23:24:50.566Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-07-11T23:24:50.566Z"}}}}