Hi,
I created a dynamic bayesian network and want to learn the parameters from data(time series). My network contains a hidden node(discrete state), so it's not observable. How can I do this in GeNIe ?
Thanks.
Best Regards,
JohnYu
How to learn DBN parameters with incomplete data
Thanks for your reply.
I don't know how DBN parameters learning works.
May I expand the dynamic model for required time slice and preprocess the data for the format and then use GeNIe's parameter learning?
For example, if I expand the model to 3 time slice, and the raw data is
" 3 4 2 1 5 6 7 2 4 5 3", then the data need to be transformed as
"3 4 2", "2 1 5", "5 6 7", " 7 2 4", "4 5 3", totally five records.
If the model have markov property, the the model will be expand to two time slice. Is that right?
Thanks.
I don't know how DBN parameters learning works.
May I expand the dynamic model for required time slice and preprocess the data for the format and then use GeNIe's parameter learning?
For example, if I expand the model to 3 time slice, and the raw data is
" 3 4 2 1 5 6 7 2 4 5 3", then the data need to be transformed as
"3 4 2", "2 1 5", "5 6 7", " 7 2 4", "4 5 3", totally five records.
If the model have markov property, the the model will be expand to two time slice. Is that right?
Thanks.