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https://issues.apache.org/jira/browse/MAHOUT-792?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13186623#comment-13186623
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Ted Dunning commented on MAHOUT-792:
------------------------------------
OK. I think I have this failing test corralled. The problem was that the test
case was reading the results and assuming the blocks in the result matrix would
be sorted. This is true on the mac and sometimes true on ubuntu. Once it
fails, it is pretty consistent.
I put a sort into test and all seems well. I replicated the failure 3 times in
a row, added the sort and verified that the failure did not occur on multiple
runs. I removed the sort and the failure returned consistently.
Fix is forthcoming shortly as soon as I do the same tests on ubuntu 10 as well
as 11.
> Add new stochastic decomposition code
> -------------------------------------
>
> Key: MAHOUT-792
> URL: https://issues.apache.org/jira/browse/MAHOUT-792
> Project: Mahout
> Issue Type: New Feature
> Reporter: Ted Dunning
> Assignee: Ted Dunning
> Fix For: 0.6
>
> Attachments: MAHOUT-792.patch, MAHOUT-792.patch, sd-2.pdf
>
>
> I have figured out some simplification for our SSVD algorithms. This
> eliminates the QR decomposition and makes life easier.
> I will produce a patch that contains the following:
> - a CholeskyDecomposition implementation that does pivoting (and thus
> rank-revealing) or not. This should actually be useful for solution of large
> out-of-core least squares problems.
> - an in-memory SSVD implementation that should work for matrices up to
> about 1/3 of available memory.
> - an out-of-core SSVD threaded implementation that should work for very
> large matrices. It should take time about equal to the cost of reading the
> input matrix 4 times and will require working disk roughly equal to the size
> of the input.
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