Model Evaluation
ICSE · Class 12 · Artificial Intelligence
Practice quiz for Model Evaluation — ICSE Class 12 Artificial Intelligence. MCQs and questions with answers to test your preparation.
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Quick Quiz: Model Evaluation
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A confusion matrix for a loan default model is [[3, 2], [2, 3]]. What is the accuracy of the model?
A confusion matrix has TP = 8, TN = 12, FP = 4, and FN = 6. What is the precision of the model?
A confusion matrix has TP = 9, FP = 3, and FN = 6. What is the recall of the model?
A model has Precision = 80% and Recall = 50%. What is its F1 Score?
Sample Questions
A model makes 75 correct predictions out of 120 total predictions. What is the accuracy?
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62.5%
Accuracy = (Number of Correct Predictions) / (Total Number of Predictions). So Accuracy = 75 / 120 = 0.625 = 62.5%.
A model has an accuracy of 82%. What is its error rate?
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18%
Error = 1 - Accuracy. If accuracy is 82%, then Error = 1 - 0.82 = 0.18 = 18%.
In a forest fire model, the model always predicts 'no fire' and the test set has 98 no-fire cases and 2 fire cases. What accuracy does the model achieve?
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98%
The model is correct on all 98 no-fire cases and wrong on both fire cases. So correct predictions = 98 and total cases = 100. Accuracy = 98/100 = 98%.
A model predicts 'fire' for every case. In 40 test cases, there are 12 actual fire cases and 28 no-fire cases. What is the precision?
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30%
If the model predicts 'fire' for every case, then TP = 12 and FP = 28. Precision = TP / (TP + FP) * 100% = 12 / (12 + 28) * 100% = 12/40 * 100% = 30%.
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