b374e0a7ab
* Make train in xgboost4j respect print params Previously no setting in params argument of Booster::train would prevent the Rabit.trackerPrint call. This can fill up a lot of screen space in the case that many folds are being trained. * Setting "silent" in this map to "true", "True", a non-zero integer, or a string that can be parsed to such an int will prevent printing. * Setting "verbose_eval" to "False" or "false" will prevent printing. * Setting "verbose_eval" to an int (or a String parseable to an int) n will result in printing every n steps, or no printing is n is zero. This is to match the python behaviour described here: https://www.kaggle.com/c/rossmann-store-sales/discussion/17499 * Fixed 'slient' typo in xgboost4j test * private access on two methods
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 release version
maven
<dependency>
<groupId>ml.dmlc</groupId>
<artifactId>xgboost4j</artifactId>
<version>latest_version_num</version>
</dependency>
sbt
"ml.dmlc" % "xgboost4j" % "latest_version_num"
For the latest release version number, please check here.
if you want to use xgboost4j-spark, you just need to replace xgboost4j with xgboost4j-spark
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"
For the latest release version number, please check here.
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:
There is an inconsistent issue between XGBoost4J-Spark and other language bindings of XGBoost.
When users use Spark to load trainingset/testset in LibSVM format with the following code snippet:
spark.read.format("libsvm").load("trainingset_libsvm")
Spark assumes that the dataset is 1-based indexed. However, when you do prediction with other bindings of XGBoost (e.g. Python API of XGBoost), XGBoost assumes that the dataset is 0-based indexed. It creates a pitfall for the users who train model with Spark but predict with the dataset in the same format in other bindings of XGBoost.