This MLS-C01 practice question tests your understanding of modeling. 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 scientist is training a binary classification model and wants to evaluate its performance using a metric that is robust to class imbalance. Which metric should be used?
Mean squared error
Why wrong: MSE is for regression, not classification.
Area under the ROC curve (AUC)
Why wrong: AUC is also robust but is not the only metric; F1 is more direct for imbalanced datasets.
F1 score
F1 score balances precision and recall and is robust to class imbalance.
Accuracy
Why wrong: Accuracy can be high even if the model ignores the minority class.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
F1 score
The F1 score is the harmonic mean of precision and recall and is robust to class imbalance because it considers both false positives and false negatives. Accuracy can be misleading with imbalanced classes.
Key principle: OSPF neighbour adjacency depends on matching area, hello/dead timers, network type, and authentication — IP reachability alone is not enough.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Mean squared error
Why it's wrong here
MSE is for regression, not classification.
Area under the ROC curve (AUC)
Why it's wrong here
AUC is also robust but is not the only metric; F1 is more direct for imbalanced datasets.
F1 score
Why this is correct
F1 score balances precision and recall and is robust to class imbalance.
Related concept
OSPF neighbours must agree on key parameters.
Accuracy
Why it's wrong here
Accuracy can be high even if the model ignores the minority class.
Common exam traps
OSPF neighbour formation depends on matching areas, timers, network type, authentication and passive-interface behaviour. Do not choose an answer only because the devices can ping.
Detailed technical explanation
OSPF questions usually test the details that control adjacency and route selection. Read the neighbour state, area, router ID and interface configuration before deciding what is wrong.
Key takeaway
OSPF neighbour adjacency depends on matching area, hello/dead timers, network type, and authentication — IP reachability alone is not enough.
Real-world example
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. OSPF neighbour adjacency depends on matching area, hello/dead timers, network type, and authentication — IP reachability alone is not enough. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Review OSPF neighbour requirements — matching area type, hello and dead timers, network type, stub flags, and authentication. Study show ip ospf neighbor states (INIT, 2-WAY, FULL). Then practise related MLS-C01 OSPF questions on adjacency and route selection.
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FAQ
Modeling — This question tests Modeling — OSPF neighbours must agree on key parameters..
The correct answer is: F1 score — The F1 score is the harmonic mean of precision and recall and is robust to class imbalance because it considers both false positives and false negatives. Accuracy can be misleading with imbalanced classes.
Review OSPF neighbour requirements — matching area type, hello and dead timers, network type, stub flags, and authentication. Study show ip ospf neighbor states (INIT, 2-WAY, FULL). Then practise related MLS-C01 OSPF questions on adjacency and route selection.
OSPF neighbours must agree on key parameters.
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Last reviewed: Jun 20, 2026
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.
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