How do I plot a ROC curve?

How do I plot a ROC curve?

To plot a ROC curve, you need the true positive rate and false positive rate from your model's predictions.

What data do I need to create the ROC curve?

You'll need the predicted probabilities of your positive class and the true labels of your data.

Can you show me an example using Python?

Sure! You can use libraries like Matplotlib and Scikit-learn. Would you like a code snippet?

Yes, please provide the code snippet.

Here's a simple example:

from sklearn.metrics import roc_curve, auc
import matplotlib.pyplot as plt

# Assuming y_true are the true labels and y_scores are the predicted probabilities
fpr, tpr, _ = roc_curve(y_true, y_scores)
roc_auc = auc(fpr, tpr)

plt.plot(fpr, tpr, label='ROC curve (area = %0.2f)' % roc_auc)
plt.plot([0, 1], [0, 1], 'k--')
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')
plt.legend(loc='lower right')
plt.show()