ml.dmlc:xgboost4j_2.11

JVM Package for XGBoost

License

License

GroupId

GroupId

ml.dmlc
ArtifactId

ArtifactId

xgboost4j_2.11
Last Version

Last Version

1.1.2
Release Date

Release Date

Type

Type

jar
Description

Description

JVM Package for XGBoost

Download xgboost4j_2.11

How to add to project

<!-- https://jarcasting.com/artifacts/ml.dmlc/xgboost4j_2.11/ -->
<dependency>
    <groupId>ml.dmlc</groupId>
    <artifactId>xgboost4j_2.11</artifactId>
    <version>1.1.2</version>
</dependency>
// https://jarcasting.com/artifacts/ml.dmlc/xgboost4j_2.11/
implementation 'ml.dmlc:xgboost4j_2.11:1.1.2'
// https://jarcasting.com/artifacts/ml.dmlc/xgboost4j_2.11/
implementation ("ml.dmlc:xgboost4j_2.11:1.1.2")
'ml.dmlc:xgboost4j_2.11:jar:1.1.2'
<dependency org="ml.dmlc" name="xgboost4j_2.11" rev="1.1.2">
  <artifact name="xgboost4j_2.11" type="jar" />
</dependency>
@Grapes(
@Grab(group='ml.dmlc', module='xgboost4j_2.11', version='1.1.2')
)
libraryDependencies += "ml.dmlc" % "xgboost4j_2.11" % "1.1.2"
[ml.dmlc/xgboost4j_2.11 "1.1.2"]

Dependencies

compile (6)

Group / Artifact Type Version
com.typesafe.akka : akka-actor_2.11 jar 2.5.23
com.esotericsoftware.kryo : kryo jar 2.22
org.scala-lang : scala-compiler jar 2.11.12
org.scala-lang : scala-reflect jar 2.11.12
org.scala-lang : scala-library jar 2.11.12
commons-logging : commons-logging jar 1.2

provided (2)

Group / Artifact Type Version
org.apache.hadoop : hadoop-hdfs jar 2.7.3
org.apache.hadoop : hadoop-common jar 2.7.3

test (4)

Group / Artifact Type Version
junit : junit jar 4.11
com.typesafe.akka : akka-testkit_2.11 jar 2.5.23
org.scalatest : scalatest_2.11 jar 3.0.8
org.scalactic : scalactic_2.11 jar 3.0.8

Project Modules

There are no modules declared in this project.

eXtreme Gradient Boosting

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Community | Documentation | Resources | Contributors | Release Notes

XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable. It implements machine learning algorithms under the Gradient Boosting framework. XGBoost provides a parallel tree boosting (also known as GBDT, GBM) that solve many data science problems in a fast and accurate way. The same code runs on major distributed environment (Kubernetes, Hadoop, SGE, MPI, Dask) and can solve problems beyond billions of examples.

License

© Contributors, 2019. Licensed under an Apache-2 license.

Contribute to XGBoost

XGBoost has been developed and used by a group of active community members. Your help is very valuable to make the package better for everyone. Checkout the Community Page.

Reference

  • Tianqi Chen and Carlos Guestrin. XGBoost: A Scalable Tree Boosting System. In 22nd SIGKDD Conference on Knowledge Discovery and Data Mining, 2016
  • XGBoost originates from research project at University of Washington.

Sponsors

Become a sponsor and get a logo here. See details at Sponsoring the XGBoost Project. The funds are used to defray the cost of continuous integration and testing infrastructure (https://xgboost-ci.net).

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Sponsors

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NVIDIA

Backers

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Other sponsors

The sponsors in this list are donating cloud hours in lieu of cash donation.

Amazon Web Services

ml.dmlc

Distributed (Deep) Machine Learning Community

A Community of Awesome Machine Learning Projects

Versions

Version
1.1.2
1.1.1
1.0.0