Bayesian network using weighted and Gibbs sampling
Bayesian network implementation using weighted and Gibbs sampling
The network example used looks like that:
The input format for that network is:
rede = BayesNet([('B', '', 0.9),
('M', '', 0.1),
('I', 'B M', {(T, T): 0.9, (T, F): 0.5, (F, T): 0.5, (F, F): 0.1}),
('G', 'B I M', {(T, T, T): 0.9, (T, T, F): 0.8, (T, F, T): 0.0, (T, F, F): 0.0, (F, T, T): 0.2, (F, T, F): 0.1, (F, F, T): 0.0, (F, F, F): 0.0}),
('J', 'G', {T: 0.9, F: 0.0}),])
You can adapt to any desired input.