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Grade 9 · Artificial intelligence

Grade 9 Artificial intelligence practice

20 questions on model evaluation. The answer key is a separate download.

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What is on the worksheet

  1. A binary classifier has TP=79 and FP=57. Calculate positive-class precision as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  2. A binary classifier has TP=79 and FP=41. Calculate positive-class precision as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  3. A binary classifier has TP=8 and FN=45. Calculate positive-class recall as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  4. A binary classifier has TP=27 and FN=61. Calculate positive-class recall as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  5. A binary classifier has TP=1 and FP=8. 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=5 and FP=43. Calculate positive-class precision as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  7. A binary classifier has TP=25 and FN=80. Calculate positive-class recall as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  8. A binary classifier has TP=31 and FN=38. 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=60 and FN=59. 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=25 and FP=40. Calculate positive-class precision as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  11. A binary classifier has TP=32 and FP=33. Calculate positive-class precision 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 FN=56. Calculate positive-class recall as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  13. A binary classifier has TP=3 and FP=83. 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=12 and FP=78. Calculate positive-class precision as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  15. A binary classifier has TP=48 and FP=30. 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=83 and FP=25. Calculate positive-class precision as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  17. A binary classifier has TP=40 and FP=70. 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=48 and FN=38. 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=74 and FP=40. Calculate positive-class precision as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  20. A binary classifier has TP=1 and FP=86. 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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