CRAN

vita 1.0.0

Variable Importance Testing Approaches

Released Dec 14, 2015 by Ender Celik

This package can be loaded by Renjin but 3 out 5 tests failed.

Dependencies

Rcpp randomForest 4.6-14

Implements the novel testing approach by Janitza et al.(2015) for the permutation variable importance measure in a random forest and the PIMP-algorithm by Altmann et al.(2010) . Janitza et al.(2015) do not use the "standard" permutation variable importance but the cross-validated permutation variable importance for the novel test approach. The cross-validated permutation variable importance is not based on the out-of-bag observations but uses a similar strategy which is inspired by the cross-validation procedure. The novel test approach can be applied for classification trees as well as for regression trees. However, the use of the novel testing approach has not been tested for regression trees so far, so this routine is meant for the expert user only and its current state is rather experimental.

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>vita</artifactId>
    <version>1.0.0-b57</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:vita')

Test Results

This package was last tested against Renjin 0.9.2687 on Aug 25, 2018.

Source

R
C++

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Release History