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https://issues.apache.org/jira/browse/MAHOUT-817?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13158986#comment-13158986
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Dmitriy Lyubimov commented on MAHOUT-817:
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ok. that's what i suspected. but i think the variance is going to depend a lot
on variance in the input (between different rows). Can you try and test how it
is going to be affected if you increase the variances of the input such that
deviation >> mean?
> 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
>
> Attachments: SSVD-PCA options.pdf, SSVD-PCA options.pdf, SSVD-PCA
> options.pdf, ssvd.m
>
>
> 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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