MLS-C01 Modeling Practice Question
A company is deploying a machine learning model for fraud detection. The model outputs a probability score. The cost of false negatives is very high. Which TWO metrics should the company focus on optimizing?
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
✓
F1 score
Recall (true positive rate) measures ability to find positives; minimizing false negatives is optimizing recall. AUC-ROC summarizes overall performance but not specific to false negatives. Precision focuses on false positives. FPR is about false positives. F1 balances precision and recall, but recall directly addresses false negatives.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Precision
Why it's wrong here
Precision focuses on false positives, not false negatives.
- ✗
False positive rate (FPR)
Why it's wrong here
FPR is about false positives, not false negatives.
- ✓
F1 score
Why this is correct
F1 = harmonic mean of precision and recall; optimizing F1 also improves recall.
- ✗
Area under the ROC curve (AUC-ROC)
Why it's wrong here
AUC-ROC is a general measure, not specific to false negatives.
- ✓
Recall
Why this is correct
Recall = TP/(TP+FN); high recall means few false negatives.
Go deeper
Related to this question
About these practice questions
Courseiva writes every MLS-C01 question from scratch — 1,672 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLS-C01 exam.