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https://issues.apache.org/jira/browse/MAHOUT-817?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13158176#comment-13158176
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Dmitriy Lyubimov commented on MAHOUT-817:
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OK so that's what I called brute force approach. Assuming we somehow know the
median, just adjust the input as we go. For column wise median we will know the
median right away. For row wise median, which I think the majority of use cases
would want to do, we will have to precompute it with one more pass. Good thing
about it is that at least it wiukd have a very little shuffle and sort
pressure, so it would practically run almost as fast as a map only job.
I think this is a very easy change.
> 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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