Hello, scikiters, Recent work by James Bergstra demonstrated that careful hyperparameter optimization, as well as careless random sampling, is often better than manual searching for many problems. You can see results in the following nips paper: http://people.fas.harvard.edu/~bergstra/files/pub/11_nips_hyperopt.pdf
I wonder if there's interest in adding some simple versions of these techniques to the scikit's very useful GridSearchCV? There is code available https://github.com/jaberg/hyperopt but it seems to be research code and it uses theano, so it's not applicable to the scikit. This could be a nice sprint project for someone. -- - Alexandre ------------------------------------------------------------------------------ RSA(R) Conference 2012 Save $700 by Nov 18 Register now http://p.sf.net/sfu/rsa-sfdev2dev1 _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
