Hi,
1) Indeed, the default scoring metrics in classification is the accuracy
2) True, the best score will be given by the best average accuracy over the
folds
3) It should raise an error as it is not a possible scorer.
Hope it help,
Arnaud Joly
On 24 Jul 2014, at 22:09, Pagliari, Roberto <rpagli...@appcomsci.com> wrote:
> I have a few comments/questions about scoring within the context of
> classification. Specifically, when GridSearchCV with kfold cross-validation
> is used.
>
> 1) From my understanding, the default scoring function is the ratio
> given by the number of correctly classified samples and the total number of
> samples.
> 2) Assuming line above is true, the score corresponding to the best
> estimator will be given by the best average score over the k partitions of
> the training data (in case k-fold is used)
> 3) By setting scoring=’confusion_matrix’ in GridSearchCV, what does it
> mean to compute the best average score? And what happens if some classes are
> missing in the data?
>
>
> Thank you,
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