CatBoost for Spark

JVM module to use CatBoost on Spark

License	The Apache License, Version 2.0
GroupId	ai.catboost
ArtifactId	catboost-spark_2.11
Last Version	0.25-rc3
Release Date	Jan 28, 2021
Type	jar
Description	CatBoost for Spark JVM module to use CatBoost on Spark
Project URL	https://catboost.ai/catboost-spark_2.11
Project Organization	CatBoost dev team

Download catboost-spark_2.11

Filename	Size
catboost-spark_2.11-0.25-rc3.pom
catboost-spark_2.11-0.25-rc3.jar	21 MB
catboost-spark_2.11-0.25-rc3-sources.jar	20 MB
catboost-spark_2.11-0.25-rc3-javadoc.jar	980 KB

How to add to project

Apache Maven

<!-- https://jarcasting.com/artifacts/ai.catboost/catboost-spark_2.11/ -->
<dependency>
    <groupId>ai.catboost</groupId>
    <artifactId>catboost-spark_2.11</artifactId>
    <version>0.25-rc3</version>
</dependency>

Gradle Groovy

// https://jarcasting.com/artifacts/ai.catboost/catboost-spark_2.11/
implementation 'ai.catboost:catboost-spark_2.11:0.25-rc3'

Gradle Kotlin

// https://jarcasting.com/artifacts/ai.catboost/catboost-spark_2.11/
implementation ("ai.catboost:catboost-spark_2.11:0.25-rc3")

Apache Buildr

'ai.catboost:catboost-spark_2.11:jar:0.25-rc3'

Apache Ivy

<dependency org="ai.catboost" name="catboost-spark_2.11" rev="0.25-rc3">
  <artifact name="catboost-spark_2.11" type="jar" />
</dependency>

Groovy Grape

@Grapes(
@Grab(group='ai.catboost', module='catboost-spark_2.11', version='0.25-rc3')
)

Scala SBT

libraryDependencies += "ai.catboost" % "catboost-spark_2.11" % "0.25-rc3"

Leiningen

[ai.catboost/catboost-spark_2.11 "0.25-rc3"]

Dependencies

compile (11)

Group / Artifact	Type	Version
com.google.guava : guava	jar	29.0-jre
commons-io : commons-io	jar	2.7
org.apache.commons : commons-lang3	jar	3.11
org.json4s : json4s-jackson_2.11	jar	3.5.3
com.fasterxml.jackson.core : jackson-databind	jar	2.6.7.3
com.fasterxml.jackson.module : jackson-module-scala_2.11	jar	2.6.7.1
io.github.classgraph : classgraph	jar	4.8.98
ai.catboost : catboost-common	jar	0.25-rc3
ai.catboost : catboost-spark-macros_2.11	jar	0.25-rc3
org.scala-lang : scala-library	jar	2.11.11
org.scala-lang : scala-reflect	jar	2.11.11

provided (5)

Group / Artifact	Type	Version
org.apache.hadoop : hadoop-mapreduce-client-core	jar	2.7.3
org.apache.hadoop : hadoop-common	jar	2.7.3
org.apache.spark : spark-core_2.11	jar	2.4.7
org.apache.spark : spark-sql_2.11	jar	2.4.7
org.apache.spark : spark-mllib_2.11	jar	2.4.7

test (3)

Group / Artifact	Type	Version
junit : junit	jar	4.11
org.scalatest : scalatest_2.11	jar	3.2.0
org.apache.commons : commons-math3	jar	3.6.1

Project Modules

There are no modules declared in this project.

Website | Documentation | Tutorials | Installation | Release Notes

CatBoost is a machine learning method based on gradient boosting over decision trees.

Main advantages of CatBoost:

• Superior quality when compared with other GBDT libraries on many datasets.
• Best in class prediction speed.
• Support for both numerical and categorical features.
• Fast GPU and multi-GPU support for training out of the box.
• Visualization tools included.

Get Started and Documentation

All CatBoost documentation is available here.

Install CatBoost by following the guide for the

• Python package
• R-package
• command line

Next you may want to investigate:

• Tutorials
• Training modes and metrics
• Cross-validation
• Parameters tuning
• Feature importance calculation
• Regular and staged predictions

If you cannot open documentation in your browser try adding yastatic.net and yastat.net to the list of allowed domains in your privacy badger.

Catboost models in production

If you want to evaluate Catboost model in your application read model api documentation.

Questions and bug reports

• For reporting bugs please use the catboost/bugreport page.
• Ask a question on Stack Overflow with the catboost tag, we monitor this for new questions.
• Seek prompt advice at Telegram group or Russian-speaking Telegram chat

Help to Make CatBoost Better

• Check out open problems and help wanted issues to see what can be improved, or open an issue if you want something.
• Add your stories and experience to Awesome CatBoost.
• To contribute to CatBoost you need to first read CLA text and add to your pull request, that you agree to the terms of the CLA. More information can be found in CONTRIBUTING.md
• Instructions for contributors can be found here.

News

Latest news are published on twitter.

Reference Paper

Anna Veronika Dorogush, Andrey Gulin, Gleb Gusev, Nikita Kazeev, Liudmila Ostroumova Prokhorenkova, Aleksandr Vorobev "Fighting biases with dynamic boosting". arXiv:1706.09516, 2017.

Anna Veronika Dorogush, Vasily Ershov, Andrey Gulin "CatBoost: gradient boosting with categorical features support". Workshop on ML Systems at NIPS 2017.

License

© YANDEX LLC, 2017-2019. Licensed under the Apache License, Version 2.0. See LICENSE file for more details.

CatBoost

CatBoost is a fast, scalable, high performance gradient boosting on decision trees library. Used for ranking, classification, regression and other ML tasks.

Versions

Version
0.25-rc3 Jan 28, 2021
0.25-rc2 Jan 18, 2021
0.25-rc1 Oct 7, 2020