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From "Dmitriy Lyubimov (Issue Comment Edited) (JIRA)" <j...@apache.org>
Subject [jira] [Issue Comment Edited] (MAHOUT-817) Add PCA options to SSVD code
Date Wed, 28 Dec 2011 00:59:30 GMT

    [ https://issues.apache.org/jira/browse/MAHOUT-817?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13176388#comment-13176388
] 

Dmitriy Lyubimov edited comment on MAHOUT-817 at 12/28/11 12:58 AM:
--------------------------------------------------------------------

btw this patch doesn't address use cases of "folding in" and "folding out" which are basically
special cases of SVD fold-in  adjusted to row-wise input and PCA offset.

Do we want to leave it out of scope? Generally it usually doesn't make sense to do this stuff
in a batch, but rather in real time which requires some indexing mechanism for V (and U).
Other than that, it is a simple multiplication operation, perhaps we could just engineer a
fold-in using regular distributed matrix operations? I never investigated an issue of a batch
fold in with Mahout.
                
      was (Author: dlyubimov):
    btw this patch doesn't address use cases of "folding in" and "folding out" which are basically
special cases of SVD fold-in  adjusted to row-wise input and PCA offset.

Do we want to leave it out of scope? Generally it usually doesn't make sense to do this stuff
in a batch, but rather in real time which requires indexing mechanism of V (and U). Other
than that, it is a simple multiplication operation, perhaps we could just engineer a fold-in
using regular distributed matrix operations? I never investigated an issue of a batch fold
in with Mahout.
                  
> 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: 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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