Hi Fred, the major difference is the optimization algorithm: Liblinear/Coordinate Descent vs. Stochastic Gradient Descent.
If your problem is high dimensional (10K or more) and you have a large number of examples (100K or more) you should choose the latter - otherwise, LogisticRegression should be fine. Both are not proper multinomial logistic regression models; LogisticRegression does not care and simply computes the probability estimates of each OVR classifier and normalized to make sure they sum to one. You could do the same for SGDClassifier(loss='log') but you have to implement it on your own. You should be aware of the fact that SGDClassifier(n_jobs > 1) uses multiple processes, thus, if your dataset (``X``) is too large (more than 50% of your RAM) you'll run into troubles. best, Peter 2012/6/15 Fred Mailhot <[email protected]>: > Dear all, > > What are the advantages of choosing one of the Subject line classifiers over > the other? At a quick glance, I see the following: > > - LogisticRegression implements predict_proba for the multiclass case, while > SGDClassifier doesn't > - SGDClassifier(loss="log") lets you specify multiple CPUs for the OVA > training, while LogisticRegression doesn't > > Are there other obvious differences that might influence this decision? > > Regards, > Fred. > > > ------------------------------------------------------------------------------ > Live Security Virtual Conference > Exclusive live event will cover all the ways today's security and > threat landscape has changed and how IT managers can respond. Discussions > will include endpoint security, mobile security and the latest in malware > threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/ > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > -- Peter Prettenhofer ------------------------------------------------------------------------------ Live Security Virtual Conference Exclusive live event will cover all the ways today's security and threat landscape has changed and how IT managers can respond. Discussions will include endpoint security, mobile security and the latest in malware threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/ _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
