I think that there are some others who could say more. On Mon, Mar 25, 2013 at 6:01 AM, Ey-Chih chow <[email protected]> wrote:
> On Mar 24, 2013, at 1:00 AM, Ted Dunning wrote: > > > - random forest, sequential and parallel implementations, new versions > are being developed, the current version may or may not be useful to you. > > > Can you elaborate the usefulness of the current version and features of > the new versions? Thanks. > > Ey-Chih Chow > > > On Mar 24, 2013, at 1:00 AM, Ted Dunning wrote: > > > You are correct to suspect that this page is substantially out of date. > > > > Currently, Mahout has the following classifiers: > > > > - stochastic gradient descent for logistic regression (SGD) with L_1 or > L_2 regularization, sequential version only. These classifiers can be > easily extended with other gradients and regularizers which should make > linear SVM's easy to implement. > > > > - naive bayes, sequential and parallel implementations > > > > - random forest, sequential and parallel implementations, new versions > are being developed, the current version may or may not be useful to you. > > > > There are a variety of other classifiers which are in various states of > utility. > > > > On Mar 24, 2013, at 4:07 AM, Chidananda Sridhar wrote: > > > >> Hi, > >> > >> I am doing a class project on classification and want to use Mahout. I > was > >> searching for the classification algorithms already implemented in > Mahout > >> and came to this page: > >> https://cwiki.apache.org/confluence/display/MAHOUT/Algorithms > >> > >> The webpage says that Online Passive > >> Aggressive< > https://cwiki.apache.org/confluence/display/MAHOUT/Online+Passive+Aggressive > >is > >> integrated and the rest of the classification algorithms are open or > >> awaiting commit. Does the webpage have the latest information, or is it > yet > >> to be updated? Is "Online Passive Aggressive" the only algorithm I can > use > >> for now? On the other hand, I see that most of the clustering algorithms > >> have been integrated. > >> > >> Thanks, > >> Chidananda > > > >
