AIF-C01 Fundamentals of AI and ML Practice Question
A team is evaluating a classification model. The confusion matrix shows: TP=80, FN=20, FP=10, TN=90. What is the precision?
⚠ Common exam trap
The AIF-C01 exam often tests the distinction between precision and recall by providing confusion matrix values that make one metric easy to miscalculate if you confuse the denominator (TP+FP vs TP+FN).
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
0.89
Precision is calculated as TP / (TP + FP). Here, TP=80 and FP=10, so precision = 80 / (80 + 10) = 80 / 90 = 0.888..., which rounds to 0.89. This metric measures the proportion of positive identifications that were actually correct.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
0.89
Why this is correct
Precision = 80/(80+10) = 0.8889 ≈ 0.89.
- ✗
0.75
Why it's wrong here
0.75 is not a standard metric from these numbers.
- ✗
0.80
Why it's wrong here
0.80 is recall (80/100), not precision.
- ✗
0.90
Why it's wrong here
0.90 is accuracy ((80+90)/(80+20+10+90)), not precision.
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