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https://issues.apache.org/jira/browse/MAHOUT-817?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Dmitriy Lyubimov updated MAHOUT-817:
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Comment: was deleted
(was: Computation of m*omega also may be fairly involved because even that it
is vector matrix multiplication, Omega is dense, bigger than input, even though
we don't have to move its input around. Maybe for big inputs we can just take a
math expectation of this. For the uniform distribution of murmur(is it
uniform?) -1,1 that is currently used we perhaps can ignore the whole m x Omega
because it converges on 0 per law of big numbers.)
> Add PCA options to SSVD code
> ----------------------------
>
> Key: MAHOUT-817
> URL: https://issues.apache.org/jira/browse/MAHOUT-817
> Project: Mahout
> Issue Type: New Feature
> Affects Versions: 0.6
> Reporter: Dmitriy Lyubimov
> Assignee: Dmitriy Lyubimov
> Fix For: Backlog
>
>
> It seems that a simple solution should exist to integrate PCA mean
> subtraction into SSVD algorithm without making it a pre-requisite step and
> also avoiding densifying the big input.
> Several approaches were suggested:
> 1) subtract mean off B
> 2) propagate mean vector deeper into algorithm algebraically where the data
> is already collapsed to smaller matrices
> 3) --?
> It needs some math done first . I'll take a stab at 1 and 2 but thoughts and
> math are welcome.
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