Re: [jira] Updated: (MAHOUT-228) Need sequential logistic regression implementation using SGD techniques

[Ted Dunning <te...@gmail.com>]

This patch looks like it might be ready to commit.  I have a test in there
that actually demonstrates real learning and which correlates fairly closely
to an R replication.

If I don't hear comments in a day or so, I will assume that silence implies
consent.

On Fri, Jun 4, 2010 at 11:44 PM, Ted Dunning (JIRA) <ji...@apache.org> wrote:

>
>     [
> https://issues.apache.org/jira/browse/MAHOUT-228?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel]
>
> Ted Dunning updated MAHOUT-228:
> -------------------------------
>
>    Attachment: MAHOUT-228.patch
>
> Updated patch
>
> > 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,
> 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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