How do I visualize a ROC curve for my model?

How do I visualize a ROC curve for my model?

To visualize a ROC curve, you can use libraries like Matplotlib or Seaborn in Python. Do you have a specific dataset in mind?

Yes, I have a binary classification dataset. What steps should I follow?

First, you'll need to calculate the true positive rate and false positive rate. Then, you can plot these rates using Matplotlib. Would you like a code example?

Yes, please provide a code example!

Here's a simple example:

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

# Assuming y_true and y_scores are your true labels and predicted scores
fpr, tpr, thresholds = roc_curve(y_true, y_scores)
plt.plot(fpr, tpr)
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('ROC Curve')
plt.show()