Hi Adam.
You can get the f_score by setting ``GridSearchCV(...,
scoring='f1_score')``.
By default, the "positive" class if the one labeled "1":
http://scikit-learn.org/dev/modules/generated/sklearn.metrics.f1_score.html#sklearn.metrics.f1_score
If you want more control, you can do
my_f_scoring = make_scorer(f1_score, pos_label="minority_label",
other_arguments=that_you_want)
GridSearchCV(..., scoring=my_f_scoring)
You can not compute accuracy and f1 score at the same time, though,
which is a known limitation, which we will fix soon.
Cheers,
Andy
On 05/08/2015 11:57 AM, Adam Goodkind wrote:
In performing a grid search, I know we can get overall accuracy, but
I'm also interested in the minority F score. Is there a way to get
that for each parameter setting combination?
Thanks,
Adam
--
*Adam Goodkind *
adamgoodkind.com <http://www.adamgoodkind.com>
@adamgreatkind <https://twitter.com/#%21/adamgreatkind>
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Widest out-of-the-box monitoring support with 50+ applications
Performance metrics, stats and reports that give you Actionable Insights
Deep dive visibility with transaction tracing using APM Insight.
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