Wait, I thought there was a patch, is there no code on this yet? The JIRA ticket says "patch available", but there's no files attached?
-jake On Wed, Dec 23, 2009 at 1:15 PM, Jake Mannix <jake.man...@gmail.com> wrote: > Hey Ted, > > I'll try out the patch, but I doubt it duplicates any of the stuff I've > got coming in - I've > been meaning to put together an SGD impl, but while ideologically it > overlaps with some > of my decomposition stuff (and the current in-memory SVD which is in Taste > is actually > of the SGD variety, so there may be some overlap with that) but any > scalable impl of > that would be awesome. > > But this patch is for SGD for logistic regression, right? How > customizable is it for > solving different plugged in optimization functions? I guess I could just > try it out and > see, eh? > > -jake > > > On Wed, Dec 23, 2009 at 12:52 PM, Ted Dunning <ted.dunn...@gmail.com>wrote: > >> Jake, >> >> I would appreciate your comments on this, especially in light of any >> duplication. >> >> David, >> >> If you have any time, your comments are always very welcome as well. >> >> On Wed, Dec 23, 2009 at 12:50 PM, Ted Dunning (JIRA) <j...@apache.org >> >wrote: >> >> > >> > [ >> > >> https://issues.apache.org/jira/browse/MAHOUT-228?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel >> ] >> > >> > Ted Dunning updated MAHOUT-228: >> > ------------------------------- >> > >> > Fix Version/s: 0.3 >> > Status: Patch Available (was: Open) >> > >> > Here is an early implementation. The learning has been implemented, but >> > not tested. Most other aspects are reasonably well tested. >> > >> > > 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 >> > > >> > > >> > > Stochastic gradient descent (SGD) is often fast enough for highly >> > scalable learning (see Vowpal Wabbit, http://hunch.net/~vw/< >> http://hunch.net/%7Evw/> >> > ). >> > > 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. >> > >> > >> >> >> -- >> Ted Dunning, CTO >> DeepDyve >> > >
