[mlpack-svn] [MLPACK] #308: GMM initial parameter values

[MLPACK Trac]

#308: GMM initial parameter values
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  Reporter:  Madda   |        Owner:        
      Type:  task    |       Status:  closed
  Priority:  major   |    Milestone:        
 Component:  mlpack  |   Resolution:  fixed 
  Keywords:          |     Blocking:        
Blocked By:          |  
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Changes (by rcurtin):

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


Comment:

 Hello Madda,

 I am in the process of writing a GMM tutorial but it is not done yet,
 unfortunately.

 You are right that the Estimate() function does not start EM from the
 values you passed in.  I have committed a fix to trunk (r16000 and r16001)
 that implement support for this by adding an extra boolean parameter to
 Estimate() that indicates that the existing model should be used as the
 initial model for the training.

 So an example might be:

 {{{
 GMM<> ml_gmm(initial_means, initial_covariances, initial_weights);

 ml_gmm.Estimate(data, 1, true); // true indicates to use the current model
 is the initial model
 }}}

 You can either update to the current svn version, or drop the four files I
 have attached (em_fit.hpp, em_fit_impl.hpp, gmm.hpp, and gmm_impl.hpp) in
 the src/mlpack/methods/gmm/ directory, overwriting the ones that came with
 mlpack 1.0.7.

 Let me know if you have any problems.

 Thanks,

 Ryan

-- 
Ticket URL: <http://trac.research.cc.gatech.edu/fastlab/ticket/308#comment:1>
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MLPACK is an intuitive, fast, and scalable C++ machine learning library developed at Georgia Tech.