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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.
Getting started
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Package details |
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| Author | Eugene Dubossarsky (project leader, chief designer), Yuriy Tyshetskiy (design, implementation, testing) |
| Maintainer | Yuriy Tyshetskiy <yuriy.tyshetskiy@nicta.com.au> |
| License | GPL-2 |
| Version | 1.1 |
| Package repository | View on CRAN |
| Installation |
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