Practice Advanced Supervised Learning & Evaluation (4) - Advanced Supervised Learning & Evaluation (Weeks 8)
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Advanced Supervised Learning & Evaluation

Practice - Advanced Supervised Learning & Evaluation

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What does the ROC curve represent?

💡 Hint: Think about what happens when you change the decision threshold.

Question 2 Easy

Define hyperparameters.

💡 Hint: Consider what settings might affect how a model trains but aren't changed automatically during training.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the main advantage of AUC as an evaluation metric?

It is easy to compute.
It is threshold-independent.
It provides a single value for accuracy.

💡 Hint: Think about what AUC tells us about model performance regardless of the threshold set.

Question 2

True or False: Increasing the complexity of a model generally prevents overfitting.

True
False

💡 Hint: Consider the balance between model fit and performance measurement.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Given a classification problem with highly imbalanced data, design a detailed analysis that compares performance using the ROC curve and Precision-Recall curve. What do you conclude?

💡 Hint: Think about which curve reveals more about the minority class performance.

Challenge 2 Hard

Select a dataset, conduct a hyperparameter tuning using both Grid Search and Random Search. Explain the differences in results and efficiency.

💡 Hint: Reflect on the significance of computational efficiency alongside performance.

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