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Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define the F1 Score.
💡 Hint: Consider its relation to the two metrics.
Question 2
Easy
What does precision measure?
💡 Hint: Think about true positives and false positives.
Practice 4 more questions and get performance evaluation
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What does the F1 Score evaluate?
💡 Hint: Consider what metrics are combined in the F1 calculation.
Question 2
True or False: The F1 Score can be misleading in balanced datasets.
💡 Hint: Think about the utility of metrics in different scenarios.
Solve and get performance evaluation
Push your limits with challenges.
Question 1
In a binary classification problem, your model predicts 70 true positives, 20 false negatives, 15 false positives, and 5 true negatives. Calculate the F1 Score and explain its significance.
💡 Hint: Make sure to calculate each part carefully before finding the F1 Score.
Question 2
Describe a scenario where the F1 Score would be more useful than accuracy alone. Provide justification.
💡 Hint: Consider situations with skewed class distributions.
Challenge and get performance evaluation