49b9f39818
* add back train method but mark as deprecated * add back train method but mark as deprecated * fix scalastyle error * fix scalastyle error * static glibc glibc++ * update to build with glib 2.12 * remove unsupported flags * update version number * remove properties * remove unnecessary command * update poms
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.
Add Maven Dependency
XGBoost4J, XGBoost4J-Spark, etc. in maven repository is compiled with g++-4.8.5
Access SNAPSHOT version
You need to add github as repo:
maven:
<repository>
<id>GitHub Repo</id>
<name>GitHub Repo</name>
<url>https://raw.githubusercontent.com/CodingCat/xgboost/maven-repo/</url>
</repository>
sbt:
resolvers += "GitHub Repo" at "https://raw.githubusercontent.com/CodingCat/xgboost/maven-repo/"
the add dependency as following:
maven
<dependency>
<groupId>ml.dmlc</groupId>
<artifactId>xgboost4j</artifactId>
<version>latest_version_num</version>
</dependency>
sbt
"ml.dmlc" % "xgboost4j" % "latest_version_num"
if you want to use xgboost4j-spark, you just need to replace xgboost4j with xgboost4j-spark
Examples
Full code examples for Scala, Java, Apache Spark, and Apache Flink can be found in the examples package.
NOTE on LIBSVM Format:
-
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
-
Whereas, use 0-based indexes format when predicting in normal mode - for instance, while using the saved model in the Python package