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c. When Precision is high and Recall is low
d. When Precision is high and Recall is high

4. In the scenario of predicting whether a team wins a match or not, what does a True Negative
represent?

a. Model predicts the team wins, and the team actually wins
b. Model predicts the team loses, and the team actually loses

c. Model predicts the team wins, but the team actually loses
d. Model predicts the team loses, but the team actually wins
5. How is the relationship between model performance and accuracy described?

a. Inversely proporti onal b. Not related
c. Directly proporti onal d. Randomly fl uctuati ng

6. Which measure is calculated by the ratio of True Positives to the sum of True Positives and False Negatives?
a. Accuracy b. Precision

c. Recall d. F1 Score
7. In a medical test for a rare disease, out of 1000 people tested, 50 actually have the disease while 950 do
not. The test correctly identifies 40 out of the 50 people with the disease as positive, but it also wrongly
identifies 30 of the healthy individuals as positive. What is the accuracy of the test?
a. 96% b. 90%

c. 85% d. 70%
8. When does overfitting occur in an AI model?

a. The model works well on the training dataset as well as on testi ng dataset
b. The model works poorly on the training dataset but good on testi ng dataset

c. The model works well on the training dataset but poorly on testi ng dataset
d. The size of training dataset is very large as compared to testi ng dataset

9. In a spam email detection system, out of 1000 emails received, 300 are spam. The system correctly
identifies 240 spam emails as spam, but it also marks 60 legitimate emails as spam. What is the precision
of the system?

a. 80% b. 70%

c. 75% d. 90%
10. How should an available dataset be divided into training and testing dataset for an AI model?
a. The testi ng dataset should be small while the training dataset should be large

b. The training dataset should be small while the testi ng dataset should be small

c. Both training and testi ng datasets should be equal in size
d. Bothe training and testi ng datasets should be small
B. Fill in the blanks.

1. The formula for Precision is True Positives divided by the sum of True Positives and ________________.
2. If Precision is high and Recall is low, then the F1 Score is ________________.

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