covidtest: covidtest Bayesian Network

In bnRep: A Repository of Bayesian Networks from the Academic Literature

covidtest Bayesian Network

Description

Discrete latent variables discovery and structure learning in mixed Bayesian networks.

Format

A conditional linear-Gaussian Bayesian network to predict the outcome of a covid test. The DAG structure was taken from the referenced paper and the probabilities learned from data (earliest version in the repository, missing data dropped). The vertices are:

asthma

(FALSE, TRUE);

autoimmune_dis

(FALSE, TRUE);

cancer

(FALSE, TRUE);

covid19_test_results

(Negative, Positive);

ctab

(FALSE, TRUE);

diabetes

(FALSE, TRUE);

diarrhea

(FALSE, TRUE);

fever

(FALSE, TRUE);

htn

(FALSE, TRUE);

labored_respiration

(FALSE, TRUE);

loss_of_taste

(FALSE, TRUE);

pulse

sob

(FALSE, TRUE);

sore_throat

(FALSE, TRUE);

temperature

Value

An object of class bn.fit. Refer to the documentation of bnlearn for details.

References

Peled, A., & Fine, S. (2021). Discrete Latent Variables Discovery and Structure Learning in Mixed Bayesian Networks. In 20th IEEE International Conference on Machine Learning and Applications (pp. 248-255). IEEE.

bnRep documentation built on April 12, 2025, 1:13 a.m.