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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 ( 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.