How can we build a ROC curve for customized ANN Model on Python?

Question

I am trying to build a customized ANN Model on Python. My method, where I have built the model, is as follows:

def binary_class(x_train,nodes,activation,n):
  #C         


        

Answer 1

Something like this should do the trick:

from sklearn import metrics

fpr, tpr, thresholds = metrics.roc_curve(true_values, predicted_values, pos_label=1)
roc_auc = metrics.auc(fpr, tpr)

lw = 2
plt.figure()
plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--', alpha=0.15)
plt.plot(fpr, tpr, lw=lw, label=f'ROC curve (area = {roc_auc: 0.2f})')

plt.xlabel('(1–Specificity) - False Positive Rate')
plt.ylabel('Sensitivity - True Positive Rate')
plt.title(f'Receiver Operating Characteristic')
plt.legend(loc="lower right")
plt.show()