History

[breaking] [jvm-packages] Remove rabit check point. (#9599 )

- Add `numBoostedRound` to jvm packages
- Remove rabit checkpoint version.
- Change the starting version of training continuation in JVM [breaking].
- Redefine the checkpoint version policy in jvm package. [breaking]
- Rename the Python check point callback parameter. [breaking]
- Unifies the checkpoint policy between Python and JVM.

2023-09-26 18:06:34 +08:00

xgboost4j

[breaking] [jvm-packages] Remove rabit check point. (#9599 )

2023-09-26 18:06:34 +08:00

xgboost4j-example

Bump version to 2.1. (#9498 )

2023-08-18 01:04:04 +08:00

xgboost4j-flink

Bump version to 2.1. (#9498 )

2023-08-18 01:04:04 +08:00

xgboost4j-gpu

Bump org.apache.commons:commons-lang3 in /jvm-packages (#9489 )

2023-08-20 00:37:15 +08:00

xgboost4j-spark

[breaking] [jvm-packages] Remove rabit check point. (#9599 )

2023-09-26 18:06:34 +08:00

xgboost4j-spark-gpu

Bump version to 2.1. (#9498 )

2023-08-18 01:04:04 +08:00

xgboost4j-tester

Scala 2.13 support. (#9099 )

2023-05-27 19:34:02 +08:00

.gitignore

Scala 2.13 support. (#9099 )

2023-05-27 19:34:02 +08:00

checkstyle-suppressions.xml

[jvm-packages] Fixed checkstyle excludes on Windows (#2370 )

2017-06-02 10:14:13 -07:00

checkstyle.xml

[jvm-packages] update checkstyle (#7335 )

2021-10-18 18:42:01 +08:00

CMakeLists.txt

[jvm-packages][xgboost4j-gpu] Support GPU dataframe and DeviceQuantileDMatrix (#7195 )

2021-09-24 14:25:00 +08:00

create_jni.py

[jvm-packages] Fix for space in sys.executable path in create_jni.py (#7358 )

2021-10-25 13:45:11 +08:00

pom.xml

Bump com.nvidia:rapids-4-spark_2.12 in /jvm-packages (#9517 )

2023-08-29 15:10:16 +08:00

README.md

Remove unmaintained jvm readme and dev scripts. (#9395 )

2023-07-18 18:23:43 +08:00

scalastyle-config.xml

[jvm-packages] update checkstyle (#7335 )

2021-10-18 18:42:01 +08:00

README.md

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 customization.
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.