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https://issues.apache.org/jira/browse/MAHOUT-228?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12848583#action_12848583
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Jake Mannix commented on MAHOUT-228:
------------------------------------

Excellent.  The only thing I did to make it compile was update SparseVector to 
RandomAccessSparseVector, and replace Functions.exp in favor of the merged 
Colt/Mahout Functions.exp.  

So it should basically be the way you left it.  Not sure why the 
TermRandomizerTest doesn't pass. 

> 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, 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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