[mlpack-svn] [MLPACK] #288: run GMM::Estimate with weighted data

[MLPACK Trac]

#288: run GMM::Estimate with weighted data
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 Reporter:  hanslovsky  |        Owner:                       
     Type:  wishlist    |       Status:  new                  
 Priority:  major       |    Milestone:                       
Component:  mlpack      |     Keywords:  GMM Estimate weighted
 Blocking:              |   Blocked By:                       
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 Having a GMM::Estimate that accepts weighted data would be a great
 enhancement of the GMM class. To make my wish more clear, I want to use
 GMM on probability maps, each voxel value in the range [0, 1]. So far we
 are doing clustering on a thresholded binary map (including all voxels
 with a value above a certain threshold). The data for the GMM  is the
 coordinates of the according voxels.
 One way of using the probability map instead of the binary map would be
 replicating the number of data points according to the probability.
 However, that would blow up the amount of data by a lot. A GMM::Estimate
 that takes the data (coordinates) and weights (probabilities) as input
 would be the best solution.
 If a solution to this already exists, please point it out to me.
 Otherwise, if a GMM with weighted data is possible, having it in mlpack
 would mean a great improvement for me.

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Ticket URL: <http://trac.research.cc.gatech.edu/fastlab/ticket/288>
MLPACK <www.fast-lab.org>
MLPACK is an intuitive, fast, and scalable C++ machine learning library developed by the FASTLAB at Georgia Tech under Dr. Alex Gray.