Inference on coronary artery desease data using bayesian networks
The Rmarkdown script in R performs the following tasks:
- Describe the dataset
- Identify a blacklist
- Learn the optimal structure of the bayesian network using score-based, constraint-based and hybrid methods, as well as model averaging
- Perform inference using bayesian networks
- Perform inference using a naive bayesian and a tree-augmented naive bayesian classifier
A Dockerfile has been added to the repository to ensure reproducibility. See https://github.com/vettorefburana/Run-Rstudio-Server-from-Docker for instructions on how to run the Docker container.
References:
Højsgaard, S., Edwards, D., & Lauritzen, S. (2012). Graphical models with R. Springer Science & Business Media. Scutari, M., & Denis, J. B. (2014). Bayesian networks: with examples in R. CRC press.