In wiki, it was wrote:
* Hidden Markov Model learning algorithms
* The learning is based on a set of observation sequences (not only one).
# K-Means learning;
# Baum-Welch learning with scaling (meaning that a learning based on long observations sequences don't generate underflows).
Can you give some tips about how use those two methods(K-Means learning and
Baum-Welch learning with scaling )to learn parameters in hmm; or you can give
me some meterials about it.
Thanks.
Original issue reported on code.google.com by shizh...@gmail.com on 6 Sep 2011 at 7:15
Original issue reported on code.google.com by
shizh...@gmail.com
on 6 Sep 2011 at 7:15