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https://issues.apache.org/jira/browse/MAHOUT-228?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12800248#action_12800248
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Ted Dunning commented on MAHOUT-228:
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We need a few things:
- a few functions should be separated out for more general utitlity
- the random vectorizer should be generalized a bit
- we need some real world testing. 20 newsgroups would be a good test as would
be rcv1. Cloning the new svm package's tests would probably be the best
short-term answer.
I, unfortunately, won't have time for a week or two to followup.
As such, perhaps the best step is to commit this now. It won't break anything.
> 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: logP.csv, MAHOUT-228-3.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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