Fwd: RE: CSparse package

[boisvert@nist.gov]

Sender: kazar001@umn.edu
Subject: RE: CSparse  package


please try JAMA for linear algebra operations.

On Aug 3 2006, Cleve Moler wrote:

>Hi --
>
>Tim Davis develops software for solving sparse systems of linear
>equations.  He does not work on eigenvalue problems.  The MATLAB sparse
>eigenvalue functions "eigs" and "svds" are based on Danny Sorensen's
>Arnoldi package, www.caam.rice.edu/software/ARPACK/.  I do not know of
>any packages in Java for sparse matrix computations of any kind, linear
>equations or eigenvalue problems.
>
>  -- Cleve Moler 
>
>-----Original Message-----
>From: jama@nist.gov [mailto:jama@nist.gov] On Behalf Of Sione
>Sent: Thursday, August 03, 2006 2:12 PM
>To: Multiple recipients of list
>Subject: CSparse package
>
>Hello Tim Davis,
>
>I have downloaded your  C/Matlab package for sparse matrix computation 
>found here to play with:
>
>http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?
>objectId=11740&objectType=FILE
>
>I will order a copy of your upcoming book ("/Direct Methods for Sparse 
>Linear Systems/") when it becomes available, but just a quick question 
>regarding your package. 
>
>What are the functions or equivalent functions  from your package that 
>correspond to  Matlab   'eigs'   and   'svds'  ?  I am no expert in  C
>
>but  I intend to port your  sparse package to Java and extend  JAMA 
>capability with sparse classes as SparseEigenDecomposition ,  
>SparseSingularValueDecomposition, etc. I find that analysis as  market 
>basket in data-mining  cannot be done via  dense-matrix  JAMA  as huge 
>"customer-by-item"  transaction matrix using non-negative matrix 
>factorisation (NNMF) will have high computational cost.   
>"Customer-by-Item"  transaction matrix is sparse therefore I think that 
>it should be done via sparse computation.
>
>Any hint would be appreciated.
>
>Thanks,
>Sione.
>
>//
>
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