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https://issues.apache.org/jira/browse/MAHOUT-817?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13158680#comment-13158680
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Dmitriy Lyubimov commented on MAHOUT-817:
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BTW is there a formal name of a vector product of a and b in a form of a new
vector (a_1 * b_1, a2 * b_2, ... a_n * b_n)?
Another problem i identified with the scheme is that Q is produced in blocks
and formation of entire row sum vector is not available at the point of B' and
BB' computation. There's one more step further in this.
> 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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