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.
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.