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From "Jake Mannix (JIRA)" <j...@apache.org>
Subject [jira] Updated: (MAHOUT-228) Need sequential logistic regression implementation using SGD techniques
Date Tue, 23 Mar 2010 06:54:27 GMT

     [ https://issues.apache.org/jira/browse/MAHOUT-228?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Jake Mannix updated MAHOUT-228:
-------------------------------

    Attachment: MAHOUT-228.patch

*bump*

I think this is now the third time I'd brought this patch up-to-date.  Compiles, but internal
tests don't pass.  Not sure why, as I haven't dug into them too deeply.

Ted, or anyone else with a desire to get Vowpal-Wabbit-style awesomeness in Mahout, want to
take this patch for a spin and see what is up with it?

Or if you, Ted, don't have time to finish it yourself, could you at least check this patch
out, and document a little about what the rest of us need to do to get this up running (and
verified as working)?

> Need sequential logistic regression implementation using SGD techniques
> -----------------------------------------------------------------------
>
>                 Key: MAHOUT-228
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-228
>             Project: Mahout
>          Issue Type: New Feature
>          Components: Classification
>            Reporter: Ted Dunning
>             Fix For: 0.4
>
>         Attachments: logP.csv, MAHOUT-228-3.patch, MAHOUT-228.patch, r.csv, sgd-derivation.pdf,
sgd-derivation.tex, sgd.csv
>
>
> Stochastic gradient descent (SGD) is often fast enough for highly scalable learning (see
Vowpal Wabbit, http://hunch.net/~vw/).
> I often need to have a logistic regression in Java as well, so that is a reasonable place
to start.

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