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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is accuracy in model evaluation?
💡 Hint: Think about how many correct predictions were made out of all predictions.
Question 2
Easy
Define precision.
💡 Hint: Remember this focuses on only the positives predicted.
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 precision measure in model evaluation?
- True positives out of all positives
- All correct predictions
- True negatives out of all negatives
💡 Hint: Recall that precision is concerned with positive predictions only.
Question 2
True or False: The F1 Score is the average of accuracy and recall.
- True
- False
💡 Hint: Think about how F1 combines precision and recall instead of including accuracy.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
You have a confusion matrix with TP=50, TN=30, FP=10, FN=10. Calculate accuracy, precision, and recall.
💡 Hint: Use the definitions of each metric to guide your calculations.
Question 2
Discuss the potential biases in AI evaluating models based exclusively on accuracy.
💡 Hint: Consider how performance metrics like precision and recall could help reveal more about a model's true effectiveness.
Challenge and get performance evaluation