XGBoost
by XGBoost Developers · open-source · Last verified 2026-03-29
XGBoost (Extreme Gradient Boosting) is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable. It implements machine learning algorithms under the Gradient Boosting framework, providing a high-performance implementation of gradient boosted decision trees.
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Specifications
- License
- Apache-2.0
- Pricing
- open-source
- Capabilities
- gradient-boosting, feature-importance, regularization, parallel-processing
- Integrations
- scikit-learn, spark, flink
- Use Cases
- fraud-detection, credit-risk-assessment, customer-churn-prediction, sales-forecasting
- API Available
- Yes
- Tags
- gradient-boosting, machine-learning, classification, regression, decision-trees
- Added
- 2026-03-29
- Completeness
- 100%
Index Score
86.5Fetch via API
Access XGBoost programmatically — pipe it into your agent, dashboard, or workflow.
curl -X GET "https://aaas.blog/api/entity/framework/xgboost" \
-H "x-api-key: aaas_your_key_here"Need an API key? Register free at /developer · Free tier: 1,000 req/day
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