algalactivity2 {bnRep} | R Documentation |
algalactivity Bayesian Networks
Description
Influence of resampling techniques on Bayesian network performance in predicting increased algal activity.
Format
A discrete Bayesian network to to predict chlorophyll-a (chl-a) using a range of water quality parameters as predictors (Fig. 7 of the referenced paper). Probabilities were given within the referenced paper. The vertices are:
- C
(0, 1);
- Chl_a
(0, 1);
- DO
(0, 1);
- N
(0, 1);
- P
(0, 1);
- pH
(0, 1);
- Te
(0, 1);
- Tu
(0, 1);
Value
An object of class bn.fit
. Refer to the documentation of bnlearn
for details.
References
Rezaabad, M. Z., Lacey, H., Marshall, L., & Johnson, F. (2023). Influence of resampling techniques on Bayesian network performance in predicting increased algal activity. Water Research, 244, 120558.
[Package bnRep version 0.0.1 Index]