I am new to Python and I notice that sklearn.metrics.r2_score is giving wrong R2 value. from sklearn.metrics import r2_score r2_score(y_true=[2,4,3,34,23], y_pred=[21,12,3,11,17]) # -0.17 r2_score(y_pred=[21,12,3,11,17], y_true=[2,4,3,34,23]) # -4.36 However, the true R2 value should be 0.002 according to the rsq function in Excel. R2 should be between 0~1. Also, switching the order of "y_true" and "y_pred" should not affect the final result. I wonder how to fix this issue? Also, "In simple linear regression (one predictor), the coefficient of determination is numerically equal to the square of the Pearson correlation coefficient". I wonder why sklearn.metrics.r2_score is different to the squared Pearson correlation coefficient in this case? Continue reading...
