BayesFusion Support Forum

Hello,

We are creating a web application for modelling competence development by students, and we are in the process of creating dynamic bayesian networks on the basis of a competence map with around a hundred nodes (about 1.5 parents per node). We are requeting support from Amazon Web Services to ...

Thank you. It is working fine. There were some misunderstandings on my side.

Certainly it was a misunderstanding on my behalf, as I had used PGMPY previously and it did exactly what I needed (for prototyping) by simply creating the dynamic network, adding the evidence and running it. This does not happens in PYSMILE, as evidence in t+n can affect beliefs in t , but it is ...

I have a situation of using some Dynamic Bayesian Networks to follow in "real time" the development of the competences of students. That means I have to update beliefs on any new evidence, as they come, so SMILE behaviour of considering all temporal evidences at once, unrolling the network, is not ...

Well, it looks like there is some differences in understanding what a DBN is. I was thinking on something that evolves in time; i.e. conditional probabilities in nodes in slice t+1 depend only on conditional probabilities in nodes in the same slice and slice t. So evidences for e_proponer = 0 and e ...

I have the opportunity to install Genie on a Windows machine, and I get a nice picture of my map:

genie[size=85][/size].png

I have followed the manual and revised the tables, and everything seems to be fine, bot the t = 0 definitions,


net.add_arc(cg, pg)
net.add_arc(cg, ag)
net.add_arc(cg ...

Thank you! I would fix my is_evidence call. The charts are created using a spreadsheets (attached). And yes, the probabilities move, but too little. Consider the first pair or evidences on value 0 for e_proponer and e_aportar, they should have moved the probabilities much more than they are, as it ...

Dear Piotr,

Thank you very much for your help. I can get the 16 time slices I wanted. However, I guess I am doing something wrong because the behaviour is not as expected. Given the temporal evidence

Competencia Tiempo Nivel
'e_proponer' 1 0
'e_aportar' 2 0
'e_proponer' 4 1
'e_aportar' 5 1
'e ...

I did the changes and it started working! Then I discovered all variables in the initial state of the net have the same probability distribution (0.5, 0.5, 0), so I initialized the top variable (CG) adding the following to my code

t = self.stream_table(cpd.flatDist(3))
net.set_node_definition(cg ...

Well, net.update_beliefs() seems to go well, but then I have problems printing the posteriors:

Network written to colaborar_din.xdsl
Starting inferencing...
Posteriors with no evidence set:
P(Colaborar_G = Bajo) = 0.5
P(Colaborar_G = Medio) = 0.5
P(Colaborar_G = Alto) = 0.0
Traceback (most recent ...

Thank you! However, I got this error message:


TypeError: add_node(): incompatible function arguments. The following argument types are supported:
1. (self: pysmile.Network, node_type: int, node_id: unicode) -> int
2. (self: pysmile.Network, node_type: int) -> int
3. (self: pysmile.Network ...

Thank you for responding. What I am trying to do is to implement a dynamic bayesian network in the following way:

I create the original network and update beliefs.
I create the 'past nodes', link them, define them with the values got in the original network (previously saved), and update the ...

Given the fact that the method to set the evidence in a node only allows to provide a given value, not a probability distribution, I wonder if there is a way to set a node state as evidence; that is to say, so that updating the beliefs do not modifies it but uses it as input to the updating process ...

Hello,

I have searched for sample code showing how to create a DBN and do some inferences with it (preferably but not necessarily in Python), and I
have found nothing. Do you know of any samples you can share with me?

Regards,
Rafael