CRAN

gbts 1.2.0

Hyperparameter Search for Gradient Boosted Trees

Released Feb 27, 2017 by Waley W. J. Liang

This package is available for Renjin and there are no known compatibility issues.

Dependencies

doRNG 1.6.6 gbm 2.1.3 doParallel 1.0.11 foreach 1.4.4 earth 4.6.2

An implementation of hyperparameter optimization for Gradient Boosted Trees on binary classification and regression problems. The current version provides two optimization methods: Bayesian optimization and random search. Instead of giving the single best model, the final output is an ensemble of Gradient Boosted Trees constructed via the method of ensemble selection.

Installation

Maven

This package can be included as a dependency from a Java or Scala project by including the following your project's pom.xml file. Read more about embedding Renjin in JVM-based projects.

<dependencies>
  <dependency>
    <groupId>org.renjin.cran</groupId>
    <artifactId>gbts</artifactId>
    <version>1.2.0-b13</version>
  </dependency>
</dependencies>
<repositories>
  <repository>
    <id>bedatadriven</id>
    <name>bedatadriven public repo</name>
    <url>https://nexus.bedatadriven.com/content/groups/public/</url>
  </repository>
</repositories>

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Renjin CLI

If you're using Renjin from the command line, you load this library by invoking:

library('org.renjin.cran:gbts')

Test Results

This package was last tested against Renjin 0.9.2622 on Apr 8, 2018.

Source

R

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Release History