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rohan-paul/multi_2.py

Created October 22, 2021 21:40
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multi_2.py
# Now generate TPR, FPR and ROC data
tpr,fpr,roc_auc = ([[]]*number_of_classes for _ in range(3))
f,ax = plt.subplots()
for i in range(number_of_classes):
fpr[i], tpr[i], _ = roc_curve(labels==i, predictions[:, i])
roc_auc[i] = auc(fpr[i], tpr[i])
ax.plot(fpr[i],tpr[i])
plt.legend(['Class {:d}'.format(d) for d in range(number_of_classes)])
plt.xlabel('FPR')
plt.ylabel('TPR')
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