LASSO and Elastic Net (Adaptive) Penalized Least Squares, Logistic Regression, HHSVM, Squared Hinge SVM and Expectile Regression using a Fast GCD Algorithm
Released Nov 20, 2017 by Yi Yang
A generalized coordinate descent (GCD) algorithm for computing the solution path of the hybrid Huberized support vector machine (HHSVM) and its generalization, including the LASSO and elastic net (adaptive) penalized least squares, logistic regression, HHSVM, squared hinge loss SVM and expectile regression.
This package can be included as a dependency from a Java or Scala project by including
the following your project's
about embedding Renjin in JVM-based projects.
<dependencies> <dependency> <groupId>org.renjin.cran</groupId> <artifactId>gcdnet</artifactId> <version>1.0.5-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>
If you're using Renjin from the command line, you load this library by invoking:
This package was last tested against Renjin 0.9.2709 on Nov 8, 2018.