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Grade 10 · Artificial intelligence

Grade 10 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=77 and FN=7. Calculate positive-class recall as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  2. A binary classifier has TP=25 and FN=72. Calculate positive-class recall as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  3. 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.

  4. A binary classifier has TP=65 and FN=28. 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=80 and FN=30. Calculate positive-class recall as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  6. A binary classifier has TP=13 and FP=83. 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=38 and FP=74. 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=71 and FP=54. Calculate positive-class precision as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  9. A binary classifier has TP=63 and FN=87. 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=86 and FN=77. 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=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.

  12. A binary classifier has TP=72 and FP=40. 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=21 and FN=14. Calculate positive-class recall as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.

  14. A binary classifier has TP=64 and FN=40. 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=86 and FP=44. 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=2 and FN=53. 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=74 and FP=53. 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=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.

  19. A binary classifier has TP=63 and FN=31. 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=33 and FP=66. 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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