Practice Key Metrics (7.5.2) - AI Project Cycle - CBSE 12 AI (Artificial Intelligence)

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6 sample questions

Question 1.
Define Accuracy.
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Think about all the predictions made by the model.
Question 2.
What does Precision measure?
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It focuses on the accuracy of positive predictions.
3Question 3.
What does Accuracy measure?
- Total correct predictions
- Total false predictions
- True positives only
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Think about how many choices were entirely correct.
4Question 4.
Precision focuses on which aspect?
- Overall predictions
- Correctness of predicted positives
- Total negatives
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Remember, it defines the quality of positive identifications.
Question 5.
Suppose you have a dataset with a class imbalance where 90% are negatives and only 10% are positives. If your model predicts all of them as negative, what would be the accuracy, precision, recall, and F1 Score?
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Calculate each metric based on the confusion matrix components.
Question 6.
Analyze a classification model that generates the following confusion matrix: TP=25, TN=15, FP=5, FN=5. What are the accuracy, precision, recall, and F1 score?
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Follow the definitions of each metric to guide your computations.

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