diabetes {bnRep} | R Documentation |
ciabetes Bayesian Network
Description
Sensitivity and robustness analysis in Bayesian networks with the bnmonitor R package.
Format
A discrete Bayesian network to predict whether or not a patient has diabetes, based on certain diagnostic measurements. The Bayesian network is learned as in the referenced paper. The vertices are:
- AGE
Age (Low, High);
- DIAB
Test for diabetes (Neg, Pos);
- GLUC
Plasma glucose concentration (Low, High);
- INS
2-hour serum insulin (Low, High);
- MASS
Body mass index (Low, High);
- PED
Diabetes pedigree function (Low, High);
- PREG
Number of times pregnant (Low, High);
- PRES
Diastolic blood pressure (Low, High);
- TRIC
Triceps skin fold thickness (Low, High);
Value
An object of class bn.fit
. Refer to the documentation of bnlearn
for details.
References
Leonelli, M., Ramanathan, R., & Wilkerson, R. L. (2023). Sensitivity and robustness analysis in Bayesian networks with the bnmonitor R package. Knowledge-Based Systems, 278, 110882.