A Shiny Application for End-to-End Bayesian Decision Network Analysis and Web-Deployment

A Shiny application for learning Bayesian Decision Networks from data. This package can be used for probabilistic reasoning (in the observational setting), causal inference (in the presence of interventions) and learning policy decisions (in Decision Network setting). Functionalities include end-to-end implementations for data-preprocessing, structure-learning, exact inference, approximate inference, extending the learned structure to Decision Networks and policy optimization using statistically rigorous methods such as bootstraps, resampling, ensemble-averaging and cross-validation. In addition to Bayesian Decision Networks, it also features correlation networks, community-detection, graph visualizations, graph exports and web-deployment of the learned models as Shiny dashboards.


Reference manual

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1.0.1 by Tavpritesh Sethi, 2 months ago


Report a bug at https://github.com/SAFE-ICU/wiseR/issues

Browse source code at https://github.com/cran/wiseR

Authors: Tavpritesh Sethi [aut, cre] , Shubham Maheshwari [aut]

Documentation:   PDF Manual  

GPL-3 | file LICENSE license

Imports Rgraphviz, RBGL, graph, bnlearn, HydeNet, rhandsontable, shiny, shinydashboard, dplyr, visNetwork, shinyWidgets, missRanger, tools, shinyalert, shinycssloaders, rintrojs, arules, psych, DescTools, DT, linkcomm, igraph, parallel, shinyBS

Suggests knitr, rmarkdown, rcompanion

See at CRAN