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From "Ted Dunning (JIRA)" <j...@apache.org>
Subject [jira] Commented: (MAHOUT-228) Need sequential logistic regression implementation using SGD techniques
Date Mon, 16 Aug 2010 16:59:17 GMT

    [ https://issues.apache.org/jira/browse/MAHOUT-228?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12898988#action_12898988
] 

Ted Dunning commented on MAHOUT-228:
------------------------------------

Just committed a bunch of classifier stuff.

> 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
>            Assignee: Ted Dunning
>             Fix For: 0.4
>
>         Attachments: logP.csv, MAHOUT-228-3.patch, MAHOUT-228-interfaces.patch, MAHOUT-228.patch,
MAHOUT-228.patch, MAHOUT-228.patch, MAHOUT-228.patch, r.csv, sgd-derivation.pdf, sgd-derivation.tex,
sgd.csv, TrainLogisticTest.patch
>
>
> 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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