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 ( 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)
MaintainerYuriy Tyshetskiy <>
Package repositoryView on CRAN
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autoencoder documentation built on May 2, 2019, 5:52 a.m.