healthinsurance {bnRep} | R Documentation |
healthinsurance Bayesian Network
Description
Discrete latent variables discovery and structure learning in mixed Bayesian networks.
Format
A conditional linear-Gaussian Bayesian network to predict health insurance charges. The DAG structure was taken from the referenced paper and the probabilities learned from data. The vertices are:
- age
- bmi
- charges
- children
(0, 1, 2, 3, 4, 5)
- region
(northeast, northwest, southeast, southwest);
- sex
(female, male);
- smoker
(no, yes);
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.
[Package bnRep version 0.0.1 Index]