Hi Ted, thanks for your reply. I'm trying a new model where I want to estimate the output as a timespan quantified in number of seconds, which is not bounded. That's why I think I'd use linear regression instead of logistic regression. (lemme know if i'm wrong)
I started on the code yesterday. The new AbstractOnlineLinearRegression class is implementing the OnlineLearner interface. I updated the classify() function to use linear model. I tried to follow the format for AbstractOnlineLogisticRegression. I think since linear regression can be implemented w/ sgd, the train() and regularize() functions would look similar. I'm not sure if i'm on the right path. Any advice would be helpful. Thanks On Wed, Oct 20, 2010 at 3:34 PM, Ted Dunning <[email protected]> wrote: > Frank, > > Sorry I didn't answer your previous email regarding this. > > It sounded to me like your application would actually be happier with a > form > of logistic regression. > > Perhaps we should talk some more about this on the list. > > If you want a normal linear regression, the current OnlineLearner interface > isn't terribly appropriate since it assumes a 1 of n vector target > variable. > > If you were to extend that interface to accept a vector form of target > variable then linear regression would work (and some clever tricks would > become possible for logistic regression). > > > > On Wed, Oct 20, 2010 at 1:57 PM, Frank Wang <[email protected]> wrote: > > > Hi, > > > > I'm interested in implementing Linear Regression in Mahout. Who would be > > the > > point person for the algorithm? I'd love to discuss the implementation > > details, or to help out if anyone is working on it already :) > > > > Thanks > > >
