autoencoder: Sparse Autoencoder for Automatic Learning of Representative
Features from Unlabeled Data
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 |
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