I strongly advice raising an error. Very very very strongly. Being lax about ambiguous inputs makes prototyping and interactive usage easier: less typing, and the systems gets it right most of the time. However, it makes production use and debugging complex code much harder. Indeed, errors, that might not be related to a simple user error but might be generated by a complex framework, do not lead to exceptions, but to problems down the line.
We are not R. We require a bit more of typing, we don't have as many shortcuts and magic syntax. But we can be used in production, on big datasets. We can be used by people like Airbus to monitor failures of part in planes [*], or by many others. Yes beginners want things to 'just work', but in the long run, they are thankful for a well-thought and strict specification. Gaël [*] http://www.pyvideo.org/video/3519/scikit-learn-for-predictive-maintenance-at-airbus On Fri, May 01, 2015 at 06:51:00PM +0100, Luca Puggini wrote: > I vote for 3. > On Fri, May 1, 2015 at 6:27 PM, Andreas Mueller <t3k...@gmail.com> wrote: > Hi all. > A quick questions on future API. > What should happen if a user passes an X with shape (N,), in other words > X.ndim == 1? > This is unfortunately not really consistent in scikit-learn right now. > Three things are possible: > 1) Raise an error > 2) N = n_features, that is X contains a single sample > 3) N = n_samples, that is X has a single feature > I would think it should be N=n_samples. Gael thinks (iirc) we should raise > an error. > In the code, we currently take N=n_features in predict, decision_function, > predict_proba and transform, basically everywhere. > This is in part due to using ``check_array`` everywhere, which used the > backward-compatible (but odd) behavior of np.atleast2d. > In ``fit``it looks like all estimators assume N=n_features, apart from > DictionaryLearning, MinMaxScaler, StandardScaler, which assume > N=n_samples. > See https://github.com/scikit-learn/scikit-learn/pull/4511 for more > discussion > Obviously any change we make would mean a deprecation cycle, which will > mean warning in 0.17 and 0.18 when someone gives a 1-dim X that we'll > change something soon, and then actually change it in 0.19 (1.0?). > Andy > > ------------------------------------------------------------------------------ > One dashboard for servers and applications across Physical-Virtual-Cloud > Widest out-of-the-box monitoring support with 50+ applications > Performance metrics, stats and reports that give you Actionable Insights > Deep dive visibility with transaction tracing using APM Insight. > http://ad.doubleclick.net/ddm/clk/290420510;117567292;y > _______________________________________________ > Scikit-learn-general mailing list > Scikit-learn-general@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > ------------------------------------------------------------------------------ > One dashboard for servers and applications across Physical-Virtual-Cloud > Widest out-of-the-box monitoring support with 50+ applications > Performance metrics, stats and reports that give you Actionable Insights > Deep dive visibility with transaction tracing using APM Insight. > http://ad.doubleclick.net/ddm/clk/290420510;117567292;y > _______________________________________________ > Scikit-learn-general mailing list > Scikit-learn-general@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general -- Gael Varoquaux Researcher, INRIA Parietal NeuroSpin/CEA Saclay , Bat 145, 91191 Gif-sur-Yvette France Phone: ++ 33-1-69-08-79-68 http://gael-varoquaux.info http://twitter.com/GaelVaroquaux ------------------------------------------------------------------------------ One dashboard for servers and applications across Physical-Virtual-Cloud Widest out-of-the-box monitoring support with 50+ applications Performance metrics, stats and reports that give you Actionable Insights Deep dive visibility with transaction tracing using APM Insight. http://ad.doubleclick.net/ddm/clk/290420510;117567292;y _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
