Practice Why Evaluation Matters (7.5.4) - AI Project Cycle - CBSE 12 AI (Artificial Intelligence)

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11 questions

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6 sample questions

Question 1.
What is the purpose of evaluation in AI?
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Think about the importance of model effectiveness.
Question 2.
Define accuracy in the context of model evaluation.
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It reveals how well the model is performing overall.
3Question 3.
What does precision measure in AI evaluation?
- Correct predictions over total predictions
- Correct positive predictions out of total predicted positives
- Correct negative predictions
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Recall the definition of precision.
4Question 4.
True or False: The F1 score is a single metric that combines both precision and recall.
- True
- False
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Consider the relationship between these metrics.
Question 5.
Develop a mini case study where a bias was identified during the evaluation phase of an AI project. Explain how it was addressed.
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Reflect on previous discussions about fairness in AI.
Question 6.
Using the given metrics TP=25, TN=45, FP=10, FN=5, calculate the F1 Score and interpret its significance.
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Remember the formula for F1 score.

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