Comments for eng.kulanov.org.ua

Comment on Speeding up with repmat function (MEX version) by forward-backward algorithm in C (Mex format) | eng.kulanov.org.ua

forward-backward algorithm in C (Mex format) | eng.kulanov.org.ua — Fri, 29 Jul 2011 12:32:45 +0000

[...] the previous post we were talking about repmat function in MEX format. We can reach further improvements if replace [...]

Comment on Markov Chain (Model) Builder… by Sergey Kulanov

Sergey Kulanov — Thu, 21 Apr 2011 11:44:41 +0000

How to get P(observation|MakrovModel)
this is what we have
result=prod(reshape(A.^o,1,[]))
where
A – transition matrix;
o – is the transition matrix of the observation sequence (which can be produced by
o=full(sparse(observation(1:end-1),observation(2:end),1));)
Of course we have to add initial State o(1) probability:
result*InitProb(o(1))

But the best way is to use logarithm scale
A more elegant way to count Probability P(Observation|model)was found in PMTK by Kevin Murphy:
see
log=markovLogprob(model,data)

Comment on Linux rtl8192se driver (Fedora) by Sergey Kulanov

Sergey Kulanov — Thu, 24 Mar 2011 05:13:30 +0000

This bug was reported as https://bugzilla.redhat.com/show_bug.cgi?id=682972

For now it was solved with the update from 23.03.2011 (kde-plasma-networkmanagement-0.9-0.39.20110314.fc14)

Comment on Bayes’ Rule by Sergey Kulanov

Sergey Kulanov — Mon, 20 Sep 2010 05:45:06 +0000

P(Cause|Effect)=P(Effect|Cause)*P(Cause)/P(Effect)
That is what we have in the influenza case:
What is the probability to catch influenza, if for example, we have a cough:

P(flu|cough)=P(cough|flu)*P(flu)/P(cough)

If we have some epidemic situation so P(flu) dramatically increase and P(flu|cough) also increases.