BayesFusion Support Forum

Hi Jessy, marek wrote: With five variables, there are 10 pairs that you can give strengths to and you are reporting 13. I noticed that you have 5-3 and 3-5, 1-3 and 3-1 and also 2-2. Are these correct? To better understand this part I included the set-up from my survey, the matrix table (starting in...

I'm afraid the only way you can do this is by using SMILE. You can load the network, enter evidence of your case, update the network, and then query every node and output the values the way you want it. Please look at the programming tutorials -- it is actually quite simple to do. I hope this helps....

Let me first make sure that I understand the attached Excel spreadsheet. N means the number of survey participants and the four rows below it state how many participants judged the relationship to be "no relation", "weak relation", etc., correct? Mean summarizes the score for the...

HI Wow, Your exclusion of "Keep original" in case you have no meaningful parameters in the network is correct. EM is a heuristic/numerical algorithm that searches for the optimal assignment of parameters. Hence, it is influenced by the starting point. Uniformize makes the starting point ve...

Hi Daniel, Let me try to answer your questions: Ad 1: Generally, you should use the ROC for the abnormality that you want to detect. If you have two classes and each of them is equally interesting, you should report both ROCs. They will be complementary and highly dependent on each other but still y...

Hi Wantida, To make things, simple, the distributions in the Value tab are always marginal . Sometimes they are prior and sometimes they are posterior. The term posterior (or its synonym, a Latin term "a-posteriori") relates to the fact that it has been calculated based on some observation...

I have extended the model proposed by Tomek to produce a mixture of three Beta distributions. I have also taken the Uniform distribution outside of the mixture node to make it more explicit. It may be handier in debugging your model (in case you need it).
Cheers,

Marek

I will be glad to help. Do you mean a new variable that is a mixture of two Beta distributions? In your model, you have both a product and a sum of the Beta distributions. If you want to have a mixture, I propose to add a new variable that will define the proportions (I assumed 50/50 but this is not...

There is no theoretical limitation and the algorithms should run with 1,500 variable. Bayesian search is pretty much looking for a needle in a haystack, so please do use restarts. PC will hit the combinatoric complexity of the independence tests, so it may take a long time. My advice is to set a ver...

Yes, I think you have it right. Cheers -- Marek

The EM algorithm works quite simple -- it searches for the optimal set of parameters that will maximize the log-likelihood of the data given the model. Missing values are handled by producing the most likely values for them given the current model. This changes as the model develops. When there are ...

Here it is. Sorry for this -- we will make sure that it is a part of the next release.
Cheers,

Marek

This is actually a feature. The button gets disactivated whenever there is at least one parent that has more than two states. The reason for this is that it is sometimes desirable to change the order of states in the parent (e.g., when implementing negation, like in Noisy-MIN, or when the parent is ...

Hi Charlie, There are two ways of viewing Bayesian networks. One is that they are just representations of the joint probability distributions and the structure just represents independences. From this perspective, it does not matter what the structure is and in what directions the links are, as long...

Hi Charlie, In theory, if you have a variable in any domain, then absent is a theoretically possible state. The reason why you don't see "absent" too often is precisely because of variables that you are unwilling or unable to model. They account for the non-zero probability of "absent...