On a side note: if your dataset is that small, do you think the difference
between the two tied parameter settings will be relevant?
On Feb 19, 2015 5:44 PM, "Pagliari, Roberto" <rpagli...@appcomsci.com>
wrote:
> hi Andy,
> but in practice, how do I access the estimator from the scoring function?
>
> I'm asking this because the estimator may be an SVM or random forest or
> whatever else, with different parameter names.
>
> regarding your question, it can happen with small datasets, for example,
> UCI datasets.
>
> Thank you,
>
>
> ------------------------------
> *From:* Andy [t3k...@gmail.com]
> *Sent:* Thursday, February 19, 2015 8:18 PM
> *To:* scikit-learn-general@lists.sourceforge.net
> *Subject:* Re: [Scikit-learn-general] custom scorer with parameters
>
> Well you could penalize by epsilon times 1/C or something, if you want a
> tradeoff of complexity and accuracy.
> You do have access to the estimator in the scoring.
>
> Or you could do it manually after doing the grid-search (with refit=False).
> Really, ties shouldn't happen in practice, though. How large is your
> dataset?
>
>
> On 02/19/2015 02:23 PM, Pagliari, Roberto wrote:
>
> With SVM, I’d really to pick the C and gamma I want when multiple pairs
> have the same best CV score..
>
>
>
> *From:* Andy [mailto:t3k...@gmail.com <t3k...@gmail.com>]
> *Sent:* Thursday, February 19, 2015 4:48 PM
> *To:* scikit-learn-general@lists.sourceforge.net
> *Subject:* Re: [Scikit-learn-general] custom scorer with parameters
>
>
>
> Not really.
> The scorer should not really know that it is inside a grid-search.
> What is it you want to do?
>
> On 02/19/2015 10:18 AM, Pagliari, Roberto wrote:
>
> I'd like to implement a custom score function for grid search CV.
>
> would it be possible to get the current best parameters from within the
> score function?
>
>
>
>
>
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