Sounds good. Let me take a look. Happy holidays!!
On Dec 25, 2011, at 4:16 PM, "Dmitriy Lyubimov (Commented) (JIRA)" <[email protected]> wrote: > > [ > https://issues.apache.org/jira/browse/MAHOUT-817?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13175867#comment-13175867 > ] > > Dmitriy Lyubimov commented on MAHOUT-817: > ----------------------------------------- > > bq. Thanks for merging Dmitriy. Is there anything you need from me at this > point? > > I would always appreciate if you could poke CLI version and verify it > independently via matlab test for precision of computed singular values and V > output on a larger input. > > (I am still working on reading Mahout files into R and merging with RHadoop, > when it's done i will be able to verify larger tests with R.) > > -d > >> 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. > > -- > This message is automatically generated by JIRA. > If you think it was sent incorrectly, please contact your JIRA > administrators: > https://issues.apache.org/jira/secure/ContactAdministrators!default.jspa > For more information on JIRA, see: http://www.atlassian.com/software/jira > >
