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From Ted Dunning <ted.dunn...@gmail.com>
Subject Re: [jira] Commented: (MAHOUT-228) Need sequential logistic regression implementation using SGD techniques
Date Sat, 06 Feb 2010 16:00:53 GMT
I am going to be in and out of connectivity for several days.  Probably
won't get to this.

On Sat, Feb 6, 2010 at 3:12 AM, Robin Anil (JIRA) <jira@apache.org> wrote:

>
>    [
> https://issues.apache.org/jira/browse/MAHOUT-228?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12830506#action_12830506]
>
> Robin Anil commented on MAHOUT-228:
> -----------------------------------
>
> Hi Ted, Is there a new patch with separated randomizer?.
>
> I see lots of code checkin in oliver's git branch. Can you update the same
> as a patch here.
>
>
>
> > 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: 0.3
> >
> >         Attachments: logP.csv, MAHOUT-228-3.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/<http://hunch.net/%7Evw/>
> ).
> > I often need to have a logistic regression in Java as well, so that is a
> reasonable place to start.
>
> --
> This message is automatically generated by JIRA.
> -
> You can reply to this email to add a comment to the issue online.
>
>


-- 
Ted Dunning, CTO
DeepDyve

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