4109818b32
* add back train method but mark as deprecated * add back train method but mark as deprecated * fix scalastyle error * fix scalastyle error * add back libsvm notes
XGBoost4J: Distributed XGBoost for Scala/Java
Documentation | Resources | Release Notes
XGBoost4J is the JVM package of xgboost. It brings all the optimizations and power xgboost into JVM ecosystem.
- Train XGBoost models in scala and java with easy customizations.
- Run distributed xgboost natively on jvm frameworks such as Apache Flink and Apache Spark.
You can find more about XGBoost on Documentation and Resource Page.
Examples
Full code examples for Scala, Java, Apache Spark, and Apache Flink can be found in the examples package.
NOTE on LIBSVM Format:
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Use 1-based ascending indexes for the LIBSVM format in distributed training mode
- Spark does the internal conversion, and does not accept formats that are 0-based
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Whereas, use 0-based indexes format when predicting in normal mode - for instance, while using the saved model in the Python package