itsrainingdata/sparsebn: Learning Sparse Bayesian Networks from High-Dimensional Data

Fast methods for learning sparse Bayesian networks from high-dimensional data using sparse regularization, as described in Aragam, Gu, and Zhou (2017) <arXiv:1703.04025>. Designed to handle mixed experimental and observational data with thousands of variables with either continuous or discrete observations.

Getting started

Package details

MaintainerBryon Aragam <[email protected]>
LicenseGPL (>= 2)
Version0.0.5
URL https://github.com/itsrainingdata/sparsebn
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("itsrainingdata/sparsebn")
itsrainingdata/sparsebn documentation built on Sept. 14, 2017, 6:50 a.m.