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Grade 11 · Artificial intelligence

Grade 11 Artificial intelligence practice

20 questions on model evaluation, data for ai. The answer key is a separate download.

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What is on the worksheet

  1. A binary classifier has TP=89 and FP=64. Calculate positive-class precision as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  2. Of 80 records, 20 lack a given feature. Find its missing fraction.

  3. A binary classifier has TP=61 and FN=8. Calculate positive-class recall as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  4. A baseline makes 20 errors and a new model 15 on the same 100 cases. How many fewer errors are observed?

  5. A binary classifier has TP=10 and FP=11. Calculate positive-class precision as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  6. A binary classifier has TP=8 and FN=17. Calculate positive-class recall as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  7. A binary classifier has TP=86 and FP=11. Calculate positive-class precision as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  8. A binary classifier has TP=2 and FN=5. Calculate positive-class recall as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  9. A binary classifier has TP=57 and FN=55. Calculate positive-class recall as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  10. A binary classifier has TP=32 and FN=15. Calculate positive-class recall as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  11. A binary classifier has TP=17 and FN=48. Calculate positive-class recall as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  12. A binary classifier has TP=67 and FP=69. Calculate positive-class precision as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  13. A binary classifier has TP=75 and FP=17. Calculate positive-class precision as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  14. A binary classifier has TP=7 and FN=86. Calculate positive-class recall as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  15. A binary classifier has TP=78 and FP=7. Calculate positive-class precision as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  16. A binary classifier has TP=56 and FN=36. Calculate positive-class recall as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  17. A binary classifier has TP=6 and FP=74. Calculate positive-class precision as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  18. A binary classifier has TP=88 and FN=75. Calculate positive-class recall as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  19. A binary classifier has TP=42 and FN=42. Calculate positive-class recall as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  20. A binary classifier has TP=69 and FP=51. Calculate positive-class precision as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

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