hi Immanuel, a bonus you could add is logistic regression using L1 + L2. as well as the support of ElasticNet (also L1 + L2) using the Lars algorithm.
The benefit you could explicit is that a cython implementation would avoid data copies (as our liblinear bindings makes copies), avoid the penalization of the intercept and facilitate warm restart which would also to lead to an efficient LogisticRegressionCV class. Alex On Thu, Apr 5, 2012 at 12:19 AM, Immanuel B <[email protected]> wrote: > Hello all, > > here finally is the draft for my proposal. > https://docs.google.com/document/d/1BG7Qmf3yepwkSCngRtJHQjWg2-tX-ltWxbV-goxXudA/edit > Any remarks are greatly appreciated. > > best, > Immanuel > > ------------------------------------------------------------------------------ > Better than sec? Nothing is better than sec when it comes to > monitoring Big Data applications. Try Boundary one-second > resolution app monitoring today. Free. > http://p.sf.net/sfu/Boundary-dev2dev > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general ------------------------------------------------------------------------------ Better than sec? Nothing is better than sec when it comes to monitoring Big Data applications. Try Boundary one-second resolution app monitoring today. Free. http://p.sf.net/sfu/Boundary-dev2dev _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
