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https://issues.apache.org/jira/browse/MAHOUT-228?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12794230#action_12794230
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Ted Dunning commented on MAHOUT-228:
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This implementation is purely logistic regression. Changing to other
supervised learning algorithms shouldn't be difficult and I have made the
regularization pluggable, but I would as soon get this working as is before
adding too much generality. In particular, I have strongly used the
presumption that I can do sparse updates and lazy regularization. I don't know
how much that applies to other problems.
> 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: 0.3
>
> Attachments: MAHOUT-228-1.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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