2
$\begingroup$

I have fitted several Bayesian network models to complete training data with different local probabilistic distribution but with a fixed network structure. I want to choose only one of them. How can I go about this? I've read that I can choose the model which gives the lowest prediction error or other loss metric, as well as some goodness of fit criteria like some information criterion. But how can I tell which of these approaches are better? Thanks!

$\endgroup$
2
$\begingroup$

Check out these papers:

"Scoring functions for learning Bayesian networks" by Alexandra M. Carvalho, http://www.lx.it.pt/~asmc/pub/talks/09-TA/ta_pres.pdf

"Comparison of Score Metrics for Bayesian Network learning" by Shulin Yang and Kuo-Chu Chang, http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.93.511&rep=rep1&type=pdf

"Metrics for evaluating performance and uncertainty of Bayesian network models" by Bruce G. Marcot, http://www.fs.fed.us/pnw/pubs/journals/pnw_2012_marcot002.pdf?

| cite | improve this answer | |
$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.