Practice F1 Score (30.3.4) - Confusion Matrix - CBSE 10 AI (Artificial Intelleigence)

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8 questions

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6 questions · about 4 min · pass mark 70%. Hints available.
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2 questions · about 1 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
Define the F1 Score.
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Consider its relation to the two metrics.
Question 2.
What does precision measure?
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Think about true positives and false positives.
3Question 3.
What does the F1 Score evaluate?
- Only precision
- Only recall
- Balance between precision and recall
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Consider what metrics are combined in the F1 calculation.
4Question 4.
True or False: The F1 Score can be misleading in balanced datasets.
- True
- False
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Think about the utility of metrics in different scenarios.
Question 5.
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.
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Make sure to calculate each part carefully before finding the F1 Score.
Question 6.
Describe a scenario where the F1 Score would be more useful than accuracy alone. Provide justification.
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Consider situations with skewed class distributions.

4 more questions in this section. Enroll free to practise them all.