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From "Dmitriy Lyubimov (Commented) (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (MAHOUT-817) Add PCA options to SSVD code
Date Mon, 28 Nov 2011 05:42:40 GMT

    [ https://issues.apache.org/jira/browse/MAHOUT-817?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13158191#comment-13158191
] 

Dmitriy Lyubimov commented on MAHOUT-817:
-----------------------------------------

Still need a bit of thought how it all works with power iterations, there need to be changes
there as well 

                
> 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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