covidtest {bnRep} | R Documentation |
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.