This patch looks like it might be ready to commit. I have a test in there that actually demonstrates real learning and which correlates fairly closely to an R replication.
If I don't hear comments in a day or so, I will assume that silence implies consent. On Fri, Jun 4, 2010 at 11:44 PM, Ted Dunning (JIRA) <[email protected]> wrote: > > [ > https://issues.apache.org/jira/browse/MAHOUT-228?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel] > > Ted Dunning updated MAHOUT-228: > ------------------------------- > > Attachment: MAHOUT-228.patch > > Updated patch > > > 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, > 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. > > -- > This message is automatically generated by JIRA. > - > You can reply to this email to add a comment to the issue online. > >
