BayesFusion Support Forum

Hey,

I have a quick question regarding the algorithms used for learning and inference in DBNs. After reading these threads ( post 1 , post 2 ) my understanding is, that inference in SMILE is always based on the unrolled DBN and the selected algorithm for BNs (default: junction-tree). Parameter ...

Oh, you are right. second_training.xdsl was the wrong file. I have edited my previous post and uploaded the correct file. Sorry for the confusion. Were you able to reproduce the results?

Please find attached my Java code. I had the same results when I performed parameter learning in the GeNIe GUI.

Any idea why the initial parameters in the conditional probability tables still influence the learned parameters even though I am using "uniformize" = True ? What am I missing?

Thanks for the insights. I will stay with numeric indices then.
Checking again for other reasons, I found out that the observed difference is due to an issue in the learning procedure: I assumed by enabling "uniformize" (and disabling randomize), the previous parameters of the network did not play ...

Great, thanks a lot for the fast clarification! Manually matching the variables works now.
I did a quick test and compared a learned network in GENIE to the one learned in jSMILE .
If there are no missing values, both networks will be identical. However, if I introduce missing values both networks ...

Hey,

I want to learn parameters of a DBN using JSMILE and I am a bit confused about the data format for the method matchNetwork of the class DataSet . I expected the naming convention to be similar to the one in Genie: A, A_1, A_2, B, B_1, B_2 as stated in this post .

However, when I use the ...