TimoMatzen/RBM: Package for fitting RBM and DBN models in R.

This is a package for training Restricted Boltzman machines, stacked Reststricted Boltzmann Machines and Deep Belief Networks on binary data. All models can be trained in a supervised manner and the package includes predict functions to get model predictions on an unseen test-set. The package also includes the ReconstructRBM function that can be used to reconstruct images with either a RBM model or a stacked RBM model (unsupervised).

Getting started

Package details

AuthorTimo Matzen
MaintainerTimo Matzen <[email protected]>
LicenseMIT
Version0.0.0.9000
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("TimoMatzen/RBM")
TimoMatzen/RBM documentation built on June 2, 2018, 1:45 a.m.