What steps will reproduce the problem?
1. train separate models using positive discrete samples from different classes
2. cross-test for the highest likelihood using hmmLogprob
What is the expected output? What do you see instead?
hmmLogprob sometimes crashes when a model is tested on data that do not belong
to the same class
What version / revision of the product are you using? On what operating system?
pmtk3 nov 2010
Please provide any additional information below.
The problem is that the discretized positive samples in the training set might
not include all the possible observations for a class, but hmmFit estimates the
number of observations from the positive samples. So, if there are 8
observation symbols, but a class makes use of only the first 6, the trained
model also has 6 observation states, and cannot evaluate samples belonging to
other classes, a crucial step for classification.
Solution:
There should be an option to set the number of observations directly.
Original issue reported on code.google.com by sys64...@gmail.com on 16 Jan 2011 at 9:00
Original issue reported on code.google.com by
sys64...@gmail.com
on 16 Jan 2011 at 9:00