ROC curves for a simple CNN multi-class model

3

This worked but only for a single class.

# Compute ROC curve and ROC area for each class
test_y = y_test
y_pred = y_score

fpr, tpr, thresholds = metrics.roc_curve(y_test, y_score, pos_label=2)
roc_auc = auc(fpr, tpr)

plt.figure()
lw = 2
plt.plot(fpr, tpr, color='darkorange',
         lw=lw, label='ROC curve (area = %0.2f)' % roc_auc)
plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('Receiver operating characteristic example')
plt.legend(loc="lower right")
plt.show()
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