BauerMichael/max-min-hill-climbing-algorithm: The max-min-hill-climbing algorithm
Version 1.0

This algorithm reconstructs Bayesian Networks from observational data. Therefor it first builds the skeleton of the DAG (directed acyclic graph) with the max-min parents and children (mmpc) algorithm. Afterwards it directs the edges between the vertices with the Bayesian Dirichlet likelihood-equivalence uniform (BDeu) score. For more information on that read the report appended or "The max-min hill-climbing Bayesian network structure learning algorithm", by Ioannis Tsamardinos, Laura E. Brown & Constantin F. Aliferis.

Getting started

Package details

AuthorMichael Bauer
MaintainerMichael Bauer <[email protected]>
LicenseNo License
Version1.0
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("BauerMichael/max-min-hill-climbing-algorithm")
BauerMichael/max-min-hill-climbing-algorithm documentation built on May 28, 2017, 6:57 p.m.