Hi all. I'm trying to optimize the transition states probabilities for my
HMM. I already have set them to values which I think are pretty good.
Since I know the Baum Welch can only help with the scores and optimize
them up to a local maxima I thought of using the parameters I calculated
as a starting point. The problem is that I don't know how!
I followed the example in biojava:
....
//train the model to have uniform parameters
ModelTrainer mt = new SimpleModelTrainer();
//register the model to train
mt.registerModel(hmm);
I want to use the values already set in my hmm as the starting parameters
in the BaumWelch. I don't want to use the uniform distribution as
indicated below!
//as no other counts are being used the null weight will cause
everything to be uniform
mt.setNullModelWeight(1.0);
mt.train();
I tried adding counts and looking up examples on the net but ended up more
confused than I started. How do I use the addCounts to make this work!
Stephane Acoca
Master's Student
McGill Center for Bioinformatics
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