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July 31, 2023 02:36
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Calculating confidence interval of ROC-AUC.
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from sklearn.metrics import roc_auc_score | |
from math import sqrt | |
def roc_auc_ci(y_true, y_score, positive=1): | |
AUC = roc_auc_score(y_true, y_score) | |
N1 = sum(y_true == positive) | |
N2 = sum(y_true != positive) | |
Q1 = AUC / (2 - AUC) | |
Q2 = 2*AUC**2 / (1 + AUC) | |
SE_AUC = sqrt((AUC*(1 - AUC) + (N1 - 1)*(Q1 - AUC**2) + (N2 - 1)*(Q2 - AUC**2)) / (N1*N2)) | |
lower = AUC - 1.96*SE_AUC | |
upper = AUC + 1.96*SE_AUC | |
if lower < 0: | |
lower = 0 | |
if upper > 1: | |
upper = 1 | |
return (lower, upper) |
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