Machine Learning, Probability, Statistics, Data Science, Deep Learning.
1's). import numpy as np from sklearn.metrics import roc_auc_score y_true = np.array([0, 0, 1, 1]) y_scores = np.array([0.1, 0.4, 0.35, 0.8]) roc_auc_score(y_true, y_scores) More information:look here and here. Calculation of AUC using trapezoidal rule(sklearn uses this rule):look here Random