CRAN
autoencoder 1.1
Sparse Autoencoder for Automatic Learning of Representative Features from Unlabeled Data
Released Jul 2, 2015 by Yuriy Tyshetskiy
Implementation of the sparse autoencoder in R environment, following the notes of Andrew Ng (http://www.stanford.edu/class/archive/cs/cs294a/cs294a.1104/sparseAutoencoder.pdf). The features learned by the hidden layer of the autoencoder (through unsupervised learning of unlabeled data) can be used in constructing deep belief neural networks.
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>autoencoder</artifactId> <version>1.1-b36</version> </dependency> </dependencies> <repositories> <repository> <id>bedatadriven</id> <name>bedatadriven public repo</name> <url>https://nexus.bedatadriven.com/content/groups/public/</url> </repository> </repositories>
Renjin CLI
If you're using Renjin from the command line, you load this library by invoking:
library('org.renjin.cran:autoencoder')
Test Results
This package was last tested against Renjin 0.9.2644 on Jun 1, 2018.