[mlpack-svn] [MLPACK] #306: Use sparse AllkNN in collaborative filtering

[MLPACK Trac]

#306: Use sparse AllkNN in collaborative filtering
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 Reporter:  rcurtin  |        Owner:                           
     Type:  defect   |       Status:  new                      
 Priority:  major    |    Milestone:  mlpack 1.0.8             
Component:  mlpack   |     Keywords:  cf, allknn, sparse, spmat
 Blocking:           |   Blocked By:                           
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 The basic idea in collaborative filtering is to decompose the sparse
 rating matrix into a W and H matrix.  The current code does this, but it
 also reconstructs an approximate matrix 'rating = W * H'.  Unfortunately
 this can be very large, for situations with large numbers of users and
 items.

 I'd like to remove the dense 'rating' matrix and replace it with the
 actual sparse rating matrix.  To do this, the calls to AllkNN would have
 to be modified so that sparse input matrices could be used.
 Theoretically, it should work...

 (Mudit, I CC'ed you because you're the author of the CF code :).)

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Ticket URL: <http://trac.research.cc.gatech.edu/fastlab/ticket/306>
MLPACK <www.fast-lab.org>
MLPACK is an intuitive, fast, and scalable C++ machine learning library developed at Georgia Tech.