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---------- Forwarded message --------- 发件人： Haylee Miller <mh.nw...@gmail.com> Date: 2021年12月24日周五 21:17 Subject: There is a problem with using "r2" to calculate cross_val_score and GridSearchCV scores To: <scikit-learn@python.org> Dear sklearn developers： First of all, thank you for developing this module, it is very useful. However, recently we found a small problem in the use of cross_val_score and GridSearchCV. Using "scoring = ‘r2’" to calculate the cross_val_score and GridSearchCV scores is inconsistent with the result calculated using "metrics.r2_score". [image: 5.png] According to the principle of k-fold cross-validation, we performed manual 3-fold cross-validation and there was a big gap between the score and the result of cross_val_score. Below is the code and results of our manual verification process. [image: 1.png] [image: 2.png] [image: 3.png][image: 4.png] Theoretically, the three values in results 1-3 should be similar to the three values in cross_val_score 1 and cross_val_score 2. However, only the first value in cross_val_score 1 and cross_val_score 2 is close to the result 1-3 in figures. Why is this so, looking forward to your reply！ Finally, Merry Christmas！ Best wishes, Ma Hui
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