MLS-C01 Modeling Practice Question
A company uses an XGBoost model to predict equipment failures. The model has high precision but low recall. The business impact of a false negative is very high (missing a failure). Which action would MOST effectively increase recall while keeping precision reasonably high?
⚠ Common exam trap
The MLS-C01 exam often tests the misconception that increasing boosting rounds or regularization directly improves recall, when in fact the probability threshold is the primary lever for trading off precision and recall after training.
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
✓
Decrease the probability threshold for the positive class
Decreasing the probability threshold for the positive class means the model will classify a case as a failure at a lower predicted probability, which captures more true positives (increases recall). However, this also allows more false positives, so precision may drop, but the trade-off is acceptable given the high cost of false negatives. This is a standard post-training calibration technique for imbalanced classification problems.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the regularization parameter lambda
Why it's wrong here
Regularization reduces overfitting but may not increase recall.
- ✗
Set the objective to 'reg:squarederror'
Why it's wrong here
Changing to regression objective is inappropriate.
- ✓
Decrease the probability threshold for the positive class
Why this is correct
Lower threshold increases recall but may reduce precision.
- ✗
Increase the number of boosting rounds
Why it's wrong here
More rounds may overfit but not guarantee recall improvement.
Go deeper
Related to this question
About these practice questions
This MLS-C01 question is part of Courseiva's 1,672-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam 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.