Did anyone work on this problem (exceptions raised by classifiers in grid search) since? I would be happy to do some work to fix this problem, but would need some advice.
It seems to me like the easiest way around the issue is to wrap the call to clf.fit() in a try statement and catch the exception if one is raised. In such case, there are (at least) 2 questions: 1. Should it catch any exception or just a specific type? 2. What should go into the results table for the failing grid point? NaN? Zero? Thanks, Michal On 20/06/13 18:03, Olivier Grisel wrote: > The error message could indeed be improved but this is a pathological > case anyway. > > I would rather make the grid search fault tolerant instead of making > all the scikit-learn estimators accept invalid inputs (such as empty > dataset). > > > -- > Olivier > http://twitter.com/ogrisel - http://github.com/ogrisel > > ------------------------------------------------------------------------------ > This SF.net email is sponsored by Windows: > > Build for Windows Store. > > http://p.sf.net/sfu/windows-dev2dev > _______________________________________________ > Scikit-learn-general mailing list > Scikit-learn-general@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > ------------------------------------------------------------------------------ November Webinars for C, C++, Fortran Developers Accelerate application performance with scalable programming models. Explore techniques for threading, error checking, porting, and tuning. Get the most from the latest Intel processors and coprocessors. See abstracts and register http://pubads.g.doubleclick.net/gampad/clk?id=60136231&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
