2013/1/24 Osman Başkaya <osman.bask...@computer.org>: > Thanks Olivier. But I want to ask a question about this. Isn't it a problem > that we give such a big steps? > > I worked on Weka a bit more and it seems that Logistic Regression in scikit > is similar to Weka's LibLINEAR. I tried them on the same dataset. Results > are similar except especially accommodate. I gave the same parameter values > (C = 191, tol=0.0001, L2-regularized logistic regression, no randomization, > no normalization etc..) to both classifiers and Weka gives me 0.58, but LR > in scikit gives me 0.46. > > I am tired a bit now :)
Which version of sklearn are you using? Could you try to dump your train and test datasets in a svmlight / libsvm format (e.g. using the dump_svmlight_file utility) and then run the official liblinear executable directly on it? http://www.csie.ntu.edu.tw/~cjlin/liblinear/ https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/datasets/svmlight_format.py#L263 -- Olivier http://twitter.com/ogrisel - http://github.com/ogrisel ------------------------------------------------------------------------------ Master Visual Studio, SharePoint, SQL, ASP.NET, C# 2012, HTML5, CSS, MVC, Windows 8 Apps, JavaScript and much more. Keep your skills current with LearnDevNow - 3,200 step-by-step video tutorials by Microsoft MVPs and experts. ON SALE this month only -- learn more at: http://p.sf.net/sfu/learnnow-d2d _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
