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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
Intercept
Privacy Preserving Inference with Concrete ML
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