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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define accuracy in your own words.
💡 Hint: Think about the formula for accuracy.
Question 2
Easy
What does TP stand for in a confusion matrix?
💡 Hint: It's part of the metrics to assess positive predictions.
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 the confusion matrix specifically display?
- True positives and true negatives only
- True and false positives and negatives
- Only accuracy metrics
💡 Hint: It provides a detailed breakdown of model predictions.
Question 2
True or False: AROC AUC score of 0.5 indicates a perfect model.
- True
- False
💡 Hint: Think about the meaning of AUC in terms of performance.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Given a dataset of 100 samples with the following results: TP=30, TN=50, FP=10, FN=10, calculate the accuracy, precision, recall, F1 score, and AUC.
💡 Hint: Use the formulas discussed!
Question 2
In a scenario where you have a model that predicts a highly imbalanced dataset (95% negative class), suggest how you would evaluate the model effectively.
💡 Hint: Consider metrics that reflect both classes' performances.
Challenge and get performance evaluation