On Thursday, May 8, 2014 4:14:32 PM UTC-7, William wrote: > > I could be wrong, but I don't think the implementation of Baum-Welch > is wrong. The BM algorithm [1] using double precision numbers (which > is all the HMM algorithm in Sage uses) can lead to overflow, given the > sort of computations that are involved. >
Thanks for the reply! My understanding is that it's underflow that's more common with HMM stuff, due to all the products of small probabilities running around. In some implementations I've seen this handled by the logsumexp trick: http://machineintelligence.tumblr.com/post/4998477107/the-log-sum-exp-trick Also in the Rabiner tutorial there's a section on scaling where he talks about underflow and how to handle it. that's on page 16 (272) here: http://people.sabanciuniv.edu/berrin/cs512/reading/rabiner-tutorial-on-hmm.pdf Do you recall if you handled the underflow problem in your implementation? I haven't studied the code yet, but it seems like this could be the culprit. -- You received this message because you are subscribed to the Google Groups "sage-support" group. To unsubscribe from this group and stop receiving emails from it, send an email to sage-support+unsubscr...@googlegroups.com. To post to this group, send email to sage-support@googlegroups.com. Visit this group at http://groups.google.com/group/sage-support. For more options, visit https://groups.google.com/d/optout.
