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Posted to dev@mahout.apache.org by "Dmitriy Lyubimov (JIRA)" <ji...@apache.org> on 2011/08/29 20:22:37 UTC
[jira] [Issue Comment Edited] (MAHOUT-638) Stochastic svd's is not
handling well all cases of sparse vectors
[ https://issues.apache.org/jira/browse/MAHOUT-638?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13093049#comment-13093049 ]
Dmitriy Lyubimov edited comment on MAHOUT-638 at 8/29/11 6:21 PM:
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it's random projection multiplication Y_{i*}=A_{i*}\Omega (part of the Omega class). Since that's the only operation we ever do with Omega, i did not feel like I needed to implement the whole Matrix api for Omega; and even if i did, it would've looked as something similar except here it is optimized to re-use the same holder object (yRow).
was (Author: dlyubimov):
it's random projection multiplication Y_{i*}=A_{i*}\Omega (part of the Omega class). Since that's the only operation we ever do with Omega, i did not feel like I needed to implement the whole Matrix api for Omega; and even if i did, it would've looked as something similar except here it is optimized to re-used the same holder (yRow).
> Stochastic svd's is not handling well all cases of sparse vectors
> ------------------------------------------------------------------
>
> Key: MAHOUT-638
> URL: https://issues.apache.org/jira/browse/MAHOUT-638
> Project: Mahout
> Issue Type: Bug
> Components: Math
> Affects Versions: 0.5
> Reporter: Dmitriy Lyubimov
> Assignee: Dmitriy Lyubimov
> Fix For: 0.5
>
> Attachments: MAHOUT-622-2.patch, MAHOUT-638-2.patch, MAHOUT-638-2.patch, MAHOUT-638.patch
>
>
> The Mahout patch of the algorithm is not handling all types of sparse input efficiently. BtJob doesn't handle SequentialSparseVector in a way to pick only non-zero elements from initial input and QJob doesn't iterate over RandomAccessSparseVector correctly. With extremely sparse inputs (0.05% non-zero elements) that leads to a terrible inefficiency in the aforementioned jobs (QJob, BtJob).
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