Practice Performance Metrics (28.4) - Introduction to Model Evaluation
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Performance Metrics

Practice - Performance Metrics

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is accuracy in the context of performance metrics?

💡 Hint: Think about it as how right the model's guesses are.

Question 2 Easy

What does precision measure?

💡 Hint: How many correct positives were predicted?

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does accuracy measure in a machine learning model?

A. The number of correct predictions
B. The proportion of actual positives identified
C. The ratio of true positives to predicted positives

💡 Hint: Think about it as how often the model was right.

Question 2

True or False: F1 Score balances both precision and recall.

True
False

💡 Hint: Consider if both precision and recall can be represented together.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Your model predicted 150 instances: 80 true positives, 30 false positives, and 40 false negatives. Calculate accuracy, precision, recall, and F1 score, and interpret the results.

💡 Hint: Work through the formulas methodically.

Challenge 2 Hard

Discuss how you would adjust your model if it has high accuracy but low precision. What steps would you take?

💡 Hint: Consider what factors affect how the model makes decisions.

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