Hi Othman, Please send such comments to the mailing-list.
Thanks, Mathieu On Tue, Aug 18, 2015 at 10:03 PM, Othman Soufan <othman.sou...@gmail.com> wrote: > Greetings Guys, > > First of all, I want to thank you for the nice efforts you put in this > very usable case of building and training models i.e. the case of many > classes. > > I came through your contributed implementation to multiclass.py in > Scikit-learn. I just have a suggestion for you to consider the case when > only one testing sample is passed to decision_function "Decision function > for the OneVsOneClassifier". As for the current implementation, an > undesirable output comes since n_samples = X.shape[0] will take a number > larger than one when X is only a single list vector with some values. I may > suggest you check the shape of X before parsing it in a particular way, or > update the documentation to advise the user on a suggested way to get the > prediction for one testing sample. > > In a sense, it is true to say that usually, there is a testing set of many > samples but in a specific case of mine, it was preferable to predict sample > by sample. I overcome this by using X[0:1,:] instead of X[0,:] where X is a > testing set of several samples. > > Regards, > Othman Soufan > > PhD Candidate > Mathematical and Computer Sciences and Engineering > King Abdullah University of Science and Technology > Thuwal 23955-6900 > KAUST Mail Box # 2620 > Kingdom of Saudi Arabia > Tel.: (+966) 506134003 >
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