[jira] [Updated] (MAHOUT-817) Add PCA options to SSVD code

["Dmitriy Lyubimov (Updated) (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/MAHOUT-817?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Dmitriy Lyubimov updated MAHOUT-817:
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    Attachment:     (was: SSVD-CLI.pdf)
    
> 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: 0.7
>
>         Attachments: MAHOUT-817-RC1.patch, MAHOUT-817.patch, MAHOUT-817.patch, MAHOUT-817.patch, SSVD-PCA options.pdf, ssvd-tests.R, ssvd.R, 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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