Le 14 mars 2012 08:57, Satrajit Ghosh <[email protected]> a écrit : >> IMO We should record the fit durations and return the fastest among >> the tied models. This is model agnostic and favoring fast convergence >> is a nice feature for the user. > > > doesn't too many machine and code dependent parameters come into play that > have nothing to do with the simplicity of the model?
I am not asserting that faster models for a given accuracy level will always be the most regularized once (I am not sure this is even true, I am sure we can find counter examples). I am just asserting that faster parameter sets are a good way to arbitrarily break ties on predictive accuracy as the user will prefer using parameters that lead to faster models. -- Olivier http://twitter.com/ogrisel - http://github.com/ogrisel ------------------------------------------------------------------------------ Virtualization & Cloud Management Using Capacity Planning Cloud computing makes use of virtualization - but cloud computing also focuses on allowing computing to be delivered as a service. http://www.accelacomm.com/jaw/sfnl/114/51521223/ _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
