BayesFusion Support Forum

Hello, I have a very basic question about a posteriori inference. Once evidence has propagated is it correct to take the weighted average of the mean values of the individual outcomes to get an exact value? Instead of the MAP value. For example, if I had s_10_20 (15) s_20_30 (25) s_30_40 (35) Can I...

(This question was asked/answered before on the old forum and pity it is not accessible. Apologies for not storing the response) How do I estimate the confidence in a dataset on which my model is trained? I believe the answer was that using EM I can assign a confidence level to datasets but that is...

You told me that Genie can Learn structure from continuous variables using PC algorithm but that it doesn't learn the joint distribution of the graph. I'd just wanna make sure the data are not somehow discretized before the structure learning itself begins but that rather distribution parameters ar...

Correct, when it is a root node you can just change the prior probabilities of that node.

I think soft evidence is related to inference and not learning. I constructed an example with two nodes where initially none of the nodes have evidence (see net1.jpg). Suppose soft evidence becomes available about node 2, namely P(node2=state0)=0.2 and P(node2=state1)=0.8. This can be implemented by...

Sorry, but I don't understand what you are trying to do. Can you please elaborate?

Maybe if that is possible I could also set something like 40% true, 60% false as Evidence. But I think I need to build that using an helping additional chance node. I am right? This is called soft-evidence, but it is not supported in GeNIe (or SMILE). It is possible to implement by using an additio...

You helped me a lot so far. Yet I have not tried to average the training results as it is very complicated to do this manually. I will need to write a programm for that and yet I am not so far. But it is something I will do. Or is there a way to do the averaging automatically? For Example just let ...

Learn WetGrass_wetgrass_sprinkler_rain.txt The Node wetgrass ist correct, but the node sprinkler and the node rain changed to wrong values. I did a few test runs myself. The value of WetGrass is very precise, because all the involved variables needed to learn the cpt are observed. In case of Sprink...

You indeed found a (nasty) bug. I just fixed it and a new release of GeNIe (version 2.0.2889.0) has been uploaded to the website. Could you please give it a shot and let me know if it works? Sorry for the inconvenience and thanks for finding this bug! Do you know if the odbc connection uses the same...

BUT: Now open the WetGrass_sprinkler_cloudy.txt file in GeNIe and let GeNIe train these values. What will we get? first, no correct values. Second the values change a bit every time we train it again. My assumption is that the learning algorithm did something different than just learning. I tried t...

So, summarizing, when you generated data for just 2 out of the 4 variables (e.g., Cloudy and Sprinkler), and I assume the data for the 2 variables was complete, the results were not as good as was the case when you used counts. That doesn't make much sense, because parameter learning just uses count...

Using GeNIe, what is the intervall for the confidence-level? Is it 0...10 or 0..100 or ...? Would it be better if I start with randomized Values and then train the network again and again with the same training data, but higher confidence level? Which values do you use by your experience? There is ...

I have a large Bayesian Network. Let say I have 10 chance Nodes N0-N9. Now I could train a dataset with x rows that have no missing fields in N0-N9. But this way I have not so much data. But I have many Datasets with only some node values filled in. For example: N0, N3,N5,N6 N0,N3,N4 ... and so on ...