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Even if I don't define the scoring parameter, it scores and makes a decision for best estimator, but documentation says the default value for scoring is "None", so what is it using to score when I don't define a metric or list of metrics?

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From the User Guide:

By default, parameter search uses the score function of the estimator to evaluate a parameter setting. These are the sklearn.metrics.accuracy_score for classification and sklearn.metrics.r2_score for regression...

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  • $\begingroup$ Thank you, I didn't know they had defaults in function of classificator or regressor, just seeing "score" was driving me mad. Deep dive into he documentation is needed. $\endgroup$ – TwoPointNo May 11 at 23:29
  • $\begingroup$ Each estimator's score docstring says what it measures. But classifiers and regressors consistently use accuracy and r2, respectively. $\endgroup$ – Ben Reiniger May 12 at 1:13

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