mahout-dev mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Ted Dunning (JIRA)" <j...@apache.org>
Subject [jira] Commented: (MAHOUT-228) Need sequential logistic regression implementation using SGD techniques
Date Wed, 23 Dec 2009 21:48:29 GMT

    [ https://issues.apache.org/jira/browse/MAHOUT-228?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12794230#action_12794230
] 

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


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.

-- 
This message is automatically generated by JIRA.
-
You can reply to this email to add a comment to the issue online.


Mime
View raw message