healthinsurance: healthinsurance Bayesian Network

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

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.

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