You are right.
I guess only C (in the case of linear SVM) is the best averaged over the fold.
And once C is found, the weights over the whole training set are computed.
If that's the case, my proposal may be misleading.
Thank you,
Roberto
From: Andy [mailto:[email protected]]
Sent: Saturday, July 26, 2014 4:42 AM
To: [email protected]
Subject: Re: [Scikit-learn-general] gridSearchCV best_estimator_ best_score_
On 07/25/2014 10:30 PM, Pagliari, Roberto wrote:
Hi Andy,
Maybe it's just me, but the "left out data" threw me off. Perhaps, I would
integrate with your previous comments:
best_estimator_
estimator
Estimator that was chosen by the search, i.e. estimator which gave highest
average score (or smallest loss if specified) over the cross-validation folds.
on the left out data.
best_score_
float
Highest average score of the best_estimator computed above on the left out data.
This is not entirely correct. The "best_estimator_" is retrained on the whole
training set, while best_score_ is the average over folds.
I like your string for best_estimator_, but for best_score_ I would probably
also say "Highest average score of the best parameter setting over
cross-validation folds".
Pull request welcome. The current docstring warrants improvement I think ;)
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