XGBoost Tutorials

This section contains official tutorials inside XGBoost package. See Awesome XGBoost for more resources. Also, don’t miss the feature introductions in each package.

Contents:

• Introduction to Boosted Trees
• Introduction to Model IO
• Learning to Rank
• DART booster
• Monotonic Constraints
• Feature Interaction Constraints
• Survival Analysis with Accelerated Failure Time
• Categorical Data
• Multiple Outputs
• Random Forests(TM) in XGBoost
• Distributed XGBoost on Kubernetes
• Distributed XGBoost with XGBoost4J-Spark
• Distributed XGBoost with XGBoost4J-Spark-GPU
• Distributed XGBoost with Dask
• Distributed XGBoost with PySpark
• Distributed XGBoost with Ray
• Using XGBoost External Memory Version
• C API Tutorial
• Text Input Format of DMatrix
• Notes on Parameter Tuning
• Custom Objective and Evaluation Metric
• Advanced Usage of Custom Objectives
• Intercept
• Privacy Preserving Inference with Concrete ML