Huzzah! On Thu, Aug 19, 2010 at 12:36 AM, Ted Dunning (JIRA) <[email protected]>wrote:
> > [ > https://issues.apache.org/jira/browse/MAHOUT-228?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12900200#action_12900200] > > Ted Dunning commented on MAHOUT-228: > ------------------------------------ > > OK. > > I think that was the final commit of the basic M-228 functionality. The > results should appear in > https://hudson.apache.org/hudson/job/Mahout-Quality/204/ > > We now have a reasonable selection of alternatives for online vector > learning. This includes versions that do online cross-validation with AUC > and a version that does hyper-parameter selection and annealing using > evolutionary techniques on top of the on-line cross-validation version. > > I will be adding test cases over the next few weeks, but after the dust > clears here, I will be closing M-228. Jake should be proud. > > > 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 > > Assignee: Ted Dunning > > Fix For: 0.4 > > > > Attachments: logP.csv, MAHOUT-228-3.patch, > MAHOUT-228-interfaces.patch, MAHOUT-228.patch, MAHOUT-228.patch, > MAHOUT-228.patch, MAHOUT-228.patch, r.csv, sgd-derivation.pdf, > sgd-derivation.tex, sgd.csv, TrainLogisticTest.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. > >
