CRAN

msgl 2.3.9

Multinomial Sparse Group Lasso

Released May 8, 2019 by Niels Richard Hansen

This package can be loaded by Renjin but all tests failed. An older version of this package is more compatible with Renjin.

Dependencies

RcppArmadillo 0.9.400.2.0 sglOptim 1.3.8 Matrix 1.2-17 BH 1.69.0-1 Rcpp RcppProgress 0.4.1

Multinomial logistic regression with sparse group lasso penalty. Simultaneous feature selection and parameter estimation for classification. Suitable for high dimensional multiclass classification with many classes. The algorithm computes the sparse group lasso penalized maximum likelihood estimate. Use of parallel computing for cross validation and subsampling is supported through the 'foreach' and 'doParallel' packages. Development version is on GitHub, please report package issues on GitHub.

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>msgl</artifactId>
    <version>2.3.9-b1</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:msgl')

Test Results

This package was last tested against Renjin 0.9.2726 on May 10, 2019.

Source

R
C
C++

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Release History