Bayesian networks provide an intuitive framework for probabilistic reasoning
and its graphical nature can be interpreted quite clearly. Graph based methods
of machine learning are becoming more popular because they offer a richer model
of knowledge that can be understood by a human in a graphical format. The 'bnviewer'
is an R Package that allows the interactive visualization of Bayesian Networks.
The aim of this package is to improve the Bayesian Networks visualization over
the basic and static views offered by existing packages.

visNetwork (>= 2.0.4), bnlearn (>= 4.3), methods, igraph (>=
1.2.4)

visNetwork (>= 2.0.4), bnlearn (>= 4.3), methods, igraph (>=
1.2.4), shiny

Bayesian Networks Interactive Visualization and Explainable
Artificial Intelligence
person("Robson", "Fernandes", email = "robson.fernandes@usp.br", role = c("aut", "cre", "cph"))
visNetwork (>= 2.0.4), bnlearn (>= 4.3), methods, igraph (>=
1.2.4), shiny, assertthat, caret, e1071, graphics

Bayesian Output Analysis Program for MCMC
A menu-driven program and library of functions for carrying out
convergence diagnostics and statistical and graphical analysis of Markov
chain Monte Carlo sampling output.

Bayesian Output Analysis Program (BOA) for MCMC

A menu-driven program and library of functions for
carrying out convergence diagnostics and statistical and
graphical analysis of Markov chain Monte Carlo sampling output.

person("Brian J.", "Smith", role = c("aut", "cre"),
email = "brian-j-smith@uiowa.edu")

A Clustering Method Based on Boosting on Single Attributes
An overlap clustering algorithm for categorical ultra-dimension data.
c(person("Peng", "Zhang",
email = "pengz@zju.edu.cn",
role = c("aut")),
person("Kaixiu", "Jin",
email = "jinkaixiu@zju.edu.cn",
role = c("aut", "cre")))

Profiling of Peripheral Blood Mononuclear Cells using CyTOF
ggplot2, cytofan, dplyr, reshape2, RColorBrewer, knitr,
rmarkdown
This data package contains a subset of the Bodenmiller et al, Nat Biotech 2012 dataset for testing single cell, high dimensional analysis and visualization methods.
Yann Abraham [aut, cre],
Bernd Bodenmiller [aut]