- A
$2,500
Why wrong: Only counts false positives, ignoring false negatives.
- B
$20,500
Why wrong: Incorrect calculation; likely omitted the multiplier for false negatives.
- C
$1,020,500
Why wrong: Incorrect; may have multiplied false positives by 10000.
- D
$202,500
20 * 10000 = 200000; 5 * 500 = 2500; total = 202500.
Question 104 of 1,000
AIF-C01 AI and ML Fundamentals Practice Question
This AIF-C01 practice question tests your understanding of ai and ml fundamentals. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A data science team has trained a gradient boosting model using Amazon SageMaker to predict equipment failures. The model's confusion matrix shows 100 true negatives, 5 false positives, 20 false negatives, and 75 true positives. The cost of a false negative (missed failure) is $10,000, and the cost of a false positive (false alarm) is $500. What is the total cost of the model's predictions on this evaluation set?
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
✓
$202,500
The total cost is calculated by multiplying the number of false negatives (20) by their unit cost ($10,000) and the number of false positives (5) by their unit cost ($500), then summing these values: (20 × $10,000) + (5 × $500) = $200,000 + $2,500 = $202,500. This matches option D. The true negatives and true positives have no associated cost in this evaluation.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
$2,500
Why it's wrong here
Only counts false positives, ignoring false negatives.
- ✗
$20,500
Why it's wrong here
Incorrect calculation; likely omitted the multiplier for false negatives.
- ✗
$1,020,500
Why it's wrong here
Incorrect; may have multiplied false positives by 10000.
- ✓
$202,500
Why this is correct
20 * 10000 = 200000; 5 * 500 = 2500; total = 202500.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
AWS certification exams often test the ability to correctly apply a cost matrix to a confusion matrix, where the trap is that candidates either forget to include all misclassification costs or mistakenly assign costs to correct predictions (true positives/negatives).
Detailed technical explanation
How to think about this question
In a business cost-sensitive evaluation, the confusion matrix is used to compute a weighted cost function where only misclassifications incur penalties. This is common in predictive maintenance scenarios where false negatives (missed failures) lead to catastrophic downtime costs, while false positives (false alarms) cause unnecessary inspection expenses. The total cost metric helps data scientists tune model thresholds (e.g., via SageMaker's built-in XGBoost objective or custom loss functions) to minimize financial impact rather than just accuracy.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
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FAQ
Questions learners often ask
What does this AIF-C01 question test?
AI and ML Fundamentals — This question tests AI and ML Fundamentals — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: $202,500 — The total cost is calculated by multiplying the number of false negatives (20) by their unit cost ($10,000) and the number of false positives (5) by their unit cost ($500), then summing these values: (20 × $10,000) + (5 × $500) = $200,000 + $2,500 = $202,500. This matches option D. The true negatives and true positives have no associated cost in this evaluation.
What should I do if I get this AIF-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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