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https://issues.apache.org/jira/browse/MAHOUT-673?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Dmitriy Lyubimov updated MAHOUT-673:
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Attachment: MAHOUT-673-1.patch
Done. This is implied to go on top of not-yet-committed MAHOUT-638 patch since
it applies some changes on top. But should be fine for review.
Yes-- Omega matrix could be generalized to implement Matrix API but for now it
is kept specialized to stochastic projection. Future work may derive such
generalization for the rest of the code to use.
> Stochastic projection (SSVD) to use 64bit murmur hash to produce uniform
> distribution matrix elements
> -----------------------------------------------------------------------------------------------------
>
> Key: MAHOUT-673
> URL: https://issues.apache.org/jira/browse/MAHOUT-673
> Project: Mahout
> Issue Type: Improvement
> Affects Versions: 0.4
> Reporter: Dmitriy Lyubimov
> Assignee: Dmitriy Lyubimov
> Priority: Minor
> Fix For: 0.6
>
> Attachments: MAHOUT-673-1.patch
>
>
> So, per earlier discussion on the list: for random matrix Omega in stochastic
> projection, let's use murmur hash to generate uniformly distributed elements
> in a closed interval (-1,+1] instead of using Random.nextGaussian().
> I am not sure if there's really compelling mathematical reason to do this but
> maybe it's just faster and more inline with practice accepted in Mahout for
> all this.
> The murmur 64bit value is already in the code. I just need to figure the
> optimal way to convert it into a uniform distribution.
> Github url for this issue tree:
> https://github.com/dlyubimov/mahout-commits/branches/MAHOUT-673, pull
> requests are welcome.
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