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Posted to dev@mahout.apache.org by "Hudson (JIRA)" <ji...@apache.org> on 2010/07/25 03:38:00 UTC
[jira] Commented: (MAHOUT-228) Need sequential logistic regression
implementation using SGD techniques
[ https://issues.apache.org/jira/browse/MAHOUT-228?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12892059#action_12892059 ]
Hudson commented on MAHOUT-228:
-------------------------------
Integrated in Mahout-Quality #156 (See [http://hudson.zones.apache.org/hudson/job/Mahout-Quality/156/])
MAHOUT-228
> 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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