On Wed, Feb 20, 2013 at 7:36 AM, James Bergstra <james.bergs...@gmail.com> wrote: And who would have thought that the > Perceptron would have 8 hyper-parameters??
I think the Perceptron is not a good candidate. I'd rather choose SGDClassifier (you can thus add the loss function to the parameter space). Perceptron in scikit-learn has many parameters because it inherits from the SGDClassifier machinery. However, if you use the default options, you get the standard Perceptron (which doesn't have any hyperparameter). Since it is indeed confusing, we could remove the parameters (people who want to tune those parameters can use SGDClassifier(loss="perceptron") anyway) or at the very least update the docstring to reflect that the default options lead to the standard Perceptron. Is it possible to gain insights from the hyperparameter search? Like what parameter (or combination of parameters) contributes the most to the accuracy? Mathieu ------------------------------------------------------------------------------ Everyone hates slow websites. So do we. Make your web apps faster with AppDynamics Download AppDynamics Lite for free today: http://p.sf.net/sfu/appdyn_d2d_feb _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
