ROC Python

roc.py

#https://scikit-learn.org/stable/modules/generated/sklearn.metrics.roc_curve.html

from sklearn.metrics import roc_curve

y_true = np.array([1, 1, 2, 2])
y_pred = np.array([0.1, 0.4, 0.35, 0.8])

#pos_label é onde indica-se o valor da classe de interesse
fpr, tpr, thresholds = metrics.roc_curve(y, scores, pos_label=2)

print(fpr)
#>>>array([0. , 0. , 0.5, 0.5, 1. ])

print(tpr)
#>>>array([0. , 0.5, 0.5, 1. , 1. ])

print(thresholds)
#>>>array([1.8 , 0.8 , 0.4 , 0.35, 0.1 ])