How did you evaluate on the development set?
You should use "best_score_", not grid_search.score.
On 05/12/2016 08:07 AM, A neuman wrote:
thats actually what i did.
and the difference is way to big.
Should I do it withlout gridsearchCV? I'm just wondering why
gridsearch giving me overfitted values. I know that these are the best
params and so on... but i thought i can skip the manual part where i
test the params on my own. GridsearchCV give me just one pool of
params, if they are overfitting, i cant use gridsearchCV? Just having
problems to understand this.
On 12 May 2016 at 13:45, Olivier Grisel <olivier.gri...@ensta.org
<mailto:olivier.gri...@ensta.org>> wrote:
2016-05-12 13:02 GMT+02:00 A neuman <themagenta...@gmail.com
<mailto:themagenta...@gmail.com>>:
> Thanks for the answer!
>
> but how should i check that its overfitted or not?
Do a development / evaluation split of your dataset, for instance with
the train_test_split utility first. Then train your GridSearchCV model
on the development set and evaluate it both on the development set and
on the evaluation set. If the difference is large it means that you
are overfittng.
--
Olivier
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