Practice F1 Score - 8.6 | Chapter 8: Model Evaluation Metrics | Machine Learning Basics
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8.6 - F1 Score

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

Define F1 Score in your own words.

πŸ’‘ Hint: Consider what it balances.

Question 2

Easy

What does a high F1 Score indicate?

πŸ’‘ Hint: Think about the implications of both precision and recall being high.

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 F1 Score represent in classification problems?

  • A balance between precision and recall
  • The percentage of correct predictions
  • The rate of all positive predictions

πŸ’‘ Hint: Focus on its role in balancing two important metrics.

Question 2

True or False: The F1 Score can be high even if the model has a low recall.

  • True
  • False

πŸ’‘ Hint: Consider how F1's calculation incorporates both metrics.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

A classification model for a binary outcome has been validated with 50 true positives, 10 false positives, and 90 false negatives. Calculate the precision, recall, and F1 Score.

πŸ’‘ Hint: Use the definitions to compute each part step by step.

Question 2

You are tasked with improving a model where the current F1 Score is 0.4. Discuss strategies that could increase both precision and recall and re-evaluate.

πŸ’‘ Hint: Adjusting model parameters can shift both precision and recall.

Challenge and get performance evaluation