Hi everybody. This is about the grid_search and cross_validation modules. Often, in particular when the dataset is large or the algorithm slow, it is not feasible to do n-fold cross validation and people use a single training/validation split to find hyperparameters.
As far as I can see, this is not supported in sklearn. Do you think it should be included as an option to do grid searches? It is not really "cross" validation but I think the cross_validation module would be the right place for that. What do you think? Cheers, Andy ------------------------------------------------------------------------------ The demand for IT networking professionals continues to grow, and the demand for specialized networking skills is growing even more rapidly. Take a complimentary Learning@Cisco Self-Assessment and learn about Cisco certifications, training, and career opportunities. http://p.sf.net/sfu/cisco-dev2dev _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
