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autoencoder
View on CRAN: Click
here
Download and install autoencoder package within the R console
Install from CRAN:
install.packages("autoencoder")
Install from Github:
library("remotes")
install_github("cran/autoencoder") Install by package version:
library("remotes")
install_version("autoencoder", "1.1") Attach the package and use:
library("autoencoder")
Maintained by
Yuriy Tyshetskiy
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-05-21
Latest Update:
Description:
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.
How to cite:
Yuriy Tyshetskiy (2014). autoencoder: Sparse Autoencoder for Automatic Learning of Representative
Features from Unlabeled Data. R package version 1.1, https://cran.r-project.org/web/packages/autoencoder. Accessed 29 Oct. 2026.
Previous versions and publish date:
Other packages that cited autoencoder R package
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Other R packages that autoencoder depends,
imports, suggests or enhances
Functions, R codes and Examples using
the autoencoder R package
Some associated functions: autoencode . autoencoder-package . autoencoder_Ninput=100_Nhidden=100_rho=1e-2 . autoencoder_Ninput=100_Nhidden=25_rho=1e-2 . predict.autoencoder . training_matrix_N=1e4_Ninput=100 . visualize.hidden.units .
Some associated R codes: autoencoder.R . Full autoencoder package functions and examples
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