On Fri, Oct 28, 2011 at 11:27 PM, Olivier Grisel <[email protected]> wrote:
> This is a lot of complex boilerplate for the newcomer. Plus, that would be a waste of memory and cpu time as the grid search would re-split the data just after. Lately I've been working on large-scale algorithms where it would be very useful if I had a validation set directly in fit: fit(X, y, X_val=None, y_val=None) or fit(X, y, percent_val=0) For example, SGDClassifier could use it for early stopping (don't choose the last weight vector but the best one against the validation set) or for efficient tuning of the regularization hyperparameter. Mathieu ------------------------------------------------------------------------------ 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
