Practice Metrics Used (2.5.2) - AI PROJECT CYCLE - CBSE 9 AI (Artificial Intelligence)

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6 sample questions

Question 1.
What does accuracy measure in AI models?
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Think of it in terms of correct vs incorrect.
Question 2.
Why is precision important?
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Consider scenarios where false positives are problematic.
3Question 3.
What does accuracy refer to in AI evaluations?
- A measure of true positives
- The ratio of correct predictions to total predictions
- The model’s ability to identify false positives
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Think about what accuracy really means.
4Question 4.
True or False: Precision focuses on how many true positive predictions are made compared to all actual positives.
- True
- False
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Remember what precision considers in predictions.
Question 5.
Design a hypothetical AI model for fraud detection and explain how you would use precision and recall to evaluate its effectiveness.
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Consider real-world implications of each metric.
Question 6.
Evaluate a scenario where a confusion matrix shows high false negatives. Propose potential actions to improve model performance.
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Analyze the consequences of false negatives in your context.

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