[mlpack-svn] [MLPACK] #315: set initial state probabilities for hmm

[MLPACK Trac]

#315: set initial state probabilities for hmm
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  Reporter:  fleischhauf  |        Owner:          
      Type:  enhancement  |       Status:  reopened
  Priority:  minor        |    Milestone:          
 Component:  mlpack       |   Resolution:          
  Keywords:               |     Blocking:          
Blocked By:               |  
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Changes (by fleischhauf):

  * status:  closed => reopened
  * resolution:  fixed =>


Comment:

 Hey Ryan,
 thats not what I meant,
 usually an hidden markov model is parameterized by:
 Transition matrix A,
 Observation probabilities B,
 initial state probabilities \pi.

 like described in
 here:[http://courses.media.mit.edu/2010fall/mas622j/ProblemSets/ps4/tutorial.pdf]
 or here: [http://people.sabanciuniv.edu/~berrin/cs512/reading/rabiner-
 tutorial-on-hmm.pdf]

 or are the initial state probabilities somehow part of the transition
 matrix in the constructor ?

-- 
Ticket URL: <http://trac.research.cc.gatech.edu/fastlab/ticket/315#comment:2>
MLPACK <www.fast-lab.org>
MLPACK is an intuitive, fast, and scalable C++ machine learning library developed at Georgia Tech.