BayesFusion Support Forum

GeNIe supports validation for multiple classes. Just select the nodes containing your classes in the validation dialog. The classes do not have to be all in the same node. The results will be shown in terms of accuracy data for each of the nodes/classes, confusion matrices, then ROC and calibration ...

GeNIe does check whether distributions are normalized but there is always some tolerance because of possible rounding errors. In case of your model, the tolerance of 0.00000001 was higher than some of your probabilities :-). Thank you for making your model challenging to us -- this is the best way o...

If you are building only a BN, then every node is a chance node (by definition). Value nodes and decision nodes are parts of influence diagrams, which are extensions of BNs that model decisions explicitly. It may be a good idea for you to read one of the existing books on Bayesian networks or, at le...

Thank you very much. I will sent you both a PM for response. What puzzles me about the algorithm for predictive accuracy is the following: Consider the following network A->B and states a1,a2,a3 and b1,b2,b3 respectively. Let the CPT of B be given be such, that under any constellation of B's parent...

What you want to do is to create a model of a non-stationary process, i.e., a process in which the underlying transition probabilities change over time. DBNs that we have in GeNIe are stationary and they do not allow for what you want to do. Of course, SMILE will allow you for anything, for example ...

Tomek and I discussed your problem and we started wondering whether you really want to do what you wrote that you want to do. When dealing with multiple class nodes, it does not seem fair to enter the values of all the other classes when testing the accuracy for a given class. To us, validation with...

However, this algorithm leaves me a bit puzzled. Shouldn't it rather roll a dice and then assign a state according to the posterior distribution of the class node's state? That would seem much more adequate to me. This is an interesting idea but it seems counter-intuitive to me. Would you be willin...

I'm afraid GeNIe does not have an "undo" built in. One day we will work on this but it is not on the critical path for us now. To be safe, do save your models frequently and use Cancel if you change your mind after performing changes in property dialogs. And, lastly, stay tuned :-). Cheers...

It allows the program to use relevance reasoning, which makes calculations more efficient. The answer to your question is in GeNIe help file (the section describing parameter learning and the EM algorithm).
I hope this helps,

Marek

Brute force will not do here and your problem will be faced by any Bayesian network software. SMILE is one of the most efficient and fastest packages there are. Please note the the size of CPT grows exponentially with the number of parents and your CPT is indeed quite challenging :-). Try some techn...

This is correct -- Marek

Once you open the data file (one of the File menu choices), you will see a new menu (Data), which will contain functions for learning and validation. I assume this is what you want? -- Marek

This property is used in canonical gates, such as Noisy-MAX. They require states to be sorted from high to low or from low to high (they will accept both and just use simple negation to pick the one that they want). I hope this helps -- Marek

You should run "Test only" on your test data set. This will be precisely what you want. An alternative that you may want to consider is combining the two files into one and running one of the cross-validation methods (leave-one-out or k-fold cross-validation). This approach uses your data ...

We have it in our issue manager and will return to this. You may want to know that the ideas from color psychology have been around our team for a while. QGeNIe (we will release it as a product soon) implements precisely what you want. Here is a paper describing it: http://www.pitt.edu/~druzdzel/psf...