Practice Evaluation (7.5) - AI Project Cycle - CBSE 12 AI (Artificial Intelligence)

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10 questions

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Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
4 questions · about 3 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What is accuracy in model evaluation?
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Think about how many correct predictions were made out of all predictions.
Question 2.
Define precision.
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Remember this focuses on only the positives predicted.
3Question 3.
What does precision measure in model evaluation?
- True positives out of all positives
- All correct predictions
- True negatives out of all negatives
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Recall that precision is concerned with positive predictions only.
4Question 4.
True or False: The F1 Score is the average of accuracy and recall.
- True
- False
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Think about how F1 combines precision and recall instead of including accuracy.
Question 5.
You have a confusion matrix with TP=50, TN=30, FP=10, FN=10. Calculate accuracy, precision, and recall.
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Use the definitions of each metric to guide your calculations.
Question 6.
Discuss the potential biases in AI evaluating models based exclusively on accuracy.
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Consider how performance metrics like precision and recall could help reveal more about a model's true effectiveness.

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