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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does the ROC curve plot?
💡 Hint: Remember, TPR is also known as recall.
Question 2
Easy
What is AUC?
💡 Hint: Think about how AUC relates to ROC curves.
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
Which curve is better for evaluating imbalanced datasets?
- ROC Curve
- Precision-Recall Curve
- None
💡 Hint: Recall which class is more important in imbalanced data.
Question 2
True or False: AUC of 0.7 indicates a good classifier.
- True
- False
💡 Hint: Think about the benchmarks for AUC values.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Explain why the Precision-Recall curve is often preferred over the ROC curve when evaluating classifiers on imbalanced datasets.
💡 Hint: Think about how true negatives can affect the representation in traditional metrics.
Question 2
You have a dataset with a substantial imbalance between classes. Discuss the implications of hyperparameter tuning using Random Search versus Grid Search in this context.
💡 Hint: Consider the computational expense of exploring all parameter combinations when you suspect some have more impact.
Challenge and get performance evaluation