I believe that there is a link to this paper in the code. If not file a jira.
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.177.3514&rep=rep1&type=pdf Note also that stochastic gradient descent is a very common algorithm for large scale logistic regression. You can find the basics anywhere with a simple google search. Sent from my iPhone On Jul 1, 2013, at 11:59, qiaoresearcher <[email protected]> wrote: > Ted, > > Thanks, but I have looked into the code and found it not very clear to me. > For a given cost function, there are many ways to optimize the cost > function, eg, gradient descent, newton method. It would be much better if > the authors of Mahout code can simply put one line in some place to say: > the implementation is based on XXX paper or XXX book chapter or XXX > webpage. Otherwise it is not easy for the users to figure out what update > rule is used in the code... > > Regards, > > On Mon, Jul 1, 2013 at 3:22 AM, Ted Dunning <[email protected]> wrote: > >> Follow into the regression code itself and check the references. >> >> >> On Fri, Jun 28, 2013 at 3:35 PM, qiaoresearcher <[email protected] >>> wrote: >> >>> The logistic regression code is difficult to follow: the trainlogistic >> and >>> runlogistic part >>> >>> how the likelihood is calculated, how the weights is updated, etc >>> >>> does anyone knows who write the mahout logistic regression code? what are >>> the reference on logistic regression algorithm he was using to write the >>> code? >>> >>> thanks, >>
