autoencoder: Sparse Autoencoder for Automatic Learning of Representative Features from Unlabeled Data
Version 1.1

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.

Package details

AuthorEugene Dubossarsky (project leader, chief designer), Yuriy Tyshetskiy (design, implementation, testing)
Date of publication2015-07-02 09:09:12
MaintainerYuriy Tyshetskiy <yuriy.tyshetskiy@nicta.com.au>
LicenseGPL-2
Version1.1
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("autoencoder")

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autoencoder documentation built on May 29, 2017, 6:44 p.m.