>
> a suggestion is to make sure the "simplest" models appear first on the
> grid so it's the simplest model that gets selected.
>
how do you quantify what is simple?
cheers,
satra
>
> Alex
>
> On Wed, Mar 14, 2012 at 11:04 AM, Emanuele Olivetti
> <[email protected]> wrote:
> > Hi, As far as I understand GridSearchCV selects the parameter value with
> lower score but
> > in case of multiple parameter values having the same minimum score -
> which is not
> > infrequent in the case of small datasets - it always selects
> deterministically the first
> > one of the group. This is usually the one with lowest value among
> equivalents because we
> > usually feed ordered parameter grids to GridSearchCV. Isn't this a
> biased way of doing the
> > selection? What about picking one at random (among equivalents) each
> time in order avoid
> > bias through stochasticity? The related code is here:
> >
> https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/grid_search.py#L352Best,
> > Emanuele
> >
> >
> >
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