Practice Important Model Evaluation Terminologies (29.2)

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6 sample questions

Question 1.
Define True Positive.
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Think of it as a 'correct positive' prediction.
Question 2.
What does False Negative mean?
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Consider what happens if the prediction fails.
3Question 3.
What does True Positive refer to?
- Correctly predicts a negative outcome
- Correctly predicts a positive outcome
- Incorrectly predicts a positive outcome
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TP is always the correct action taken by the model.
4Question 4.
True or False: A False Negative means a model correctly identifies a result.
- True
- False
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Think about what went wrong with the prediction.
Question 5.
You are given a dataset with the following metrics: TP = 50, TN = 25, FP = 10, FN = 15. Compute Accuracy, Precision, and Recall. Discuss your results.
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Remember to calculate each metric step-by-step.
Question 6.
If an AI model has an F1 Score of 0.7 and Precision of 0.8, what is its Recall? Show your calculations.
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Use the relationship between F1, Precision, and Recall as your guide.

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