from sklearn.metrics import r2_score y_true = y_true = [3, -0.5, 2, 7] y_pred = [2.5, 0.0, 2, 8] r2_score(y_true, y_pred) # 结果:0.9486081370449679 r2_score(y_true, y_pred, multioutput= 'uniform_average') # 结果:0.9486081370449679 y_true = [[0.5, 1], [-1, 1], [7, -6]] y_pred = [[0, 2], [-1, 2], [8, -5]] r2_score(y_true, y_pred, multioutput='variance_weighted') # 结果:0.9382566585956417 y_true = [1, 2, 3] y_pred = [1, 2, 3] r2_score(y_true, y_pred) # 结果: 1.0 y_true = [1, 2, 3] y_pred = [2, 2, 2] r2_score(y_true, y_pred) # 结果:0.0 y_true = [1, 2, 3] # bar{y} = (1+2+3)/ 3 = 2 y_pred = [3, 2, 1] # y - hat{y}(即y_true - y_pred) = [-2, 0, 2] r2_score(y_true, y_pred) # 结果:-3.0 y_true = [[0.5, 1], [-1, 1], [7, -6]] y_pred = [[0, 2], [-1, 2], [8, -5]] r2_score(y_true, y_pred, multioutput='raw_values') # 结果:array([0.96543779, 0.90816327])