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.
| Version: | 1.1 |
| Published: | 2015-07-02 |
| Author: | Eugene Dubossarsky (project leader, chief designer), Yuriy Tyshetskiy (design, implementation, testing) |
| Maintainer: | Yuriy Tyshetskiy <yuriy.tyshetskiy at nicta.com.au> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | autoencoder results |
| Reference manual: | autoencoder.pdf |
| Package source: | autoencoder_1.1.tar.gz |
| Windows binaries: | r-devel: autoencoder_1.1.zip, r-release: autoencoder_1.1.zip, r-oldrel: autoencoder_1.1.zip |
| macOS binaries: | r-release: autoencoder_1.1.tgz, r-oldrel: autoencoder_1.1.tgz |
| Old sources: | autoencoder archive |
Please use the canonical form https://CRAN.R-project.org/package=autoencoder to link to this page.