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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 02:38:17 GMT

    [ https://issues.apache.org/jira/browse/MAHOUT-228?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12898781#action_12898781
] 

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

I am going to start committing this in stages.  The first step will be the interfaces for
classifiers in general.  This will include an interface for online vector classifier learning
and an interface for vector classification.

Patch for these will come shortly with commit shortly after that.  The intent of the patch
is to simplify review.

> 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.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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