CRAN

LogicForest 2.1.0

Logic Forest

Released Sep 19, 2014 by Bethany Wolf

This package can be loaded by Renjin but 2 out 15 tests failed.

Dependencies

CircStats 0.2-4 LogicReg 1.5.9 gtools 3.5.0 plotrix 3.7-2

Two classification ensemble methods based on logic regression models. LogForest uses a bagging approach to construct an ensemble of logic regression models. LBoost uses a combination of boosting and cross-validation to construct an ensemble of logic regression models. Both methods are used for classification of binary responses based on binary predictors and for identification of important variables and variable interactions predictive of a binary outcome.

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>LogicForest</artifactId>
    <version>2.1.0-b39</version>
  </dependency>
</dependencies>
<repositories>
  <repository>
    <id>bedatadriven</id>
    <name>bedatadriven public repo</name>
    <url>https://nexus.bedatadriven.com/content/groups/public/</url>
  </repository>
</repositories>

View build log

Renjin CLI

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

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

Test Results

This package was last tested against Renjin 0.9.2644 on Jun 2, 2018.

Source

R

View GitHub Mirror

Release History