Distributed training of XGBoost models using Scala

Note

The managed MLflow integration with Databricks on Google Cloud requires Introduction to Databricks Runtime for Machine Learning 9.1 LTS or above.

The example notebooks show how you can use XGBoost with MLlib:

• The first example shows how to embed an XGBoost model into an MLlib ML pipeline.

• The second example shows how to use MLlib cross validation to tune an XGBoost model.

XGBoost classification with ML pipeline notebook

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XGBoost regression with cross-validation notebook

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