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Can anyone give a brief explanation on what best_score_ means?

I assume the score is higher the better.

Is there a range for the score for example (0,1)?

Thanks.

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Grid-search is used to find the optimal hyperparameters of a model, which results in the most accurate predictions. The grid.best_score gives the best optimal hyperparameters. This is calculated by the average of all the cross-validation fold for a single combination of the parameters you specify in the tuned_params.

Based on best_score_, we can choose the best optimal hyperparameter for the model, giving good accuracy for the model.

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  • $\begingroup$ Is there a range for the score for example (0,1)? $\endgroup$
    – Leo
    Jul 6 at 6:14

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