Practice The Receiver Operating Characteristic (ROC) Curve and Area Under the Curve (AUC) - 4.2.1.1 | Module 4: Advanced Supervised Learning & Evaluation (Weeks 8) | Machine Learning
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Knowledge

4.2.1.1 - The Receiver Operating Characteristic (ROC) Curve and Area Under the Curve (AUC)

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does ROC stand for?

💡 Hint: Think about what the acronym represents in the context of classification.

Question 2

Easy

True or False: AUC values range from 0 to 1.

💡 Hint: Consider what AUC signifies as a performance metric.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What does a perfect classifier's AUC score equal?

  • 0.5
  • 0.75
  • 1.0

💡 Hint: Consider what a perfect classifier means in practical terms.

Question 2

True or False: Lowering the threshold will always result in a higher true positive rate.

  • True
  • False

💡 Hint: Think about how thresholds influence classification outcomes.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

You have a model with an AUC of 0.85. Briefly explain what this tells you about the model, and whether it suffices for fraud detection purposes.

💡 Hint: Consider the impacts of false negatives in fraud cases.

Question 2

Create an ROC curve using hypothetical true positive and false positive values, and explain how you would interpret the shape and area.

💡 Hint: Think about how each plotted point influences the overall evaluation of the classifier.

Challenge and get performance evaluation