Research Communication | Open Access
Volume 2021 | Communication ID 332
Volume 2021 | Communication ID 332
| The Bayesian network at the service of epidemiology |
Said Mahari, Noura Yousfi
Received |
Accepted |
Published |
March 01, 2021 |
March 10, 2021 |
March 15, 2021 |
Abstract: This involves using the Bayesian probabilistic calculation to predict the spread of an epidemic such as the coronavirus in order to be able to act effectively afterwards. The principle is simple, by basing it on the Bayes formula one can learn a probabilistic Bayesian network from the observed data and subsequently be able to make predictions. This will be very useful to us in developing a better intervention strategy. We will then be led to use methods to generate data in order to make predictions, these methods are very diverse, namely LOO (Leave One Out cross validation), Metropolis ...