Question 772 of 1,672
MLS-C01 Modeling Practice Question
A machine learning engineer is evaluating a classification model that predicts whether a transaction is fraudulent. The model outputs a probability score. The cost of a false negative (missed fraud) is 10 times higher than the cost of a false positive (false alarm). Which TWO evaluation metrics should the engineer use to tune the model? (Choose TWO.)
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
✓
F-beta score with beta = 2
Precision-Recall curve (E) is well-suited for imbalanced datasets and when the positive class (fraud) is rare; it directly evaluates the trade-off between precision and recall. F-beta score with beta = 2 (A) weights recall twice as much as precision, aligning with the higher cost of false negatives. Accuracy (B) is misleading for imbalanced data and does not incorporate costs. ROC-AUC (D) can be overly optimistic on imbalanced data and is less sensitive to the cost of false negatives. Log loss (C) measures probabilistic calibration but does not directly reflect the asymmetric cost structure.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
F-beta score with beta = 2
Why this is correct
F-beta with beta > 1 weights recall higher than precision, matching the cost structure.
- ✗
Accuracy
Why it's wrong here
Accuracy is misleading when classes are imbalanced.
- ✗
Log loss
Why it's wrong here
Log loss measures probability calibration, not directly tied to misclassification cost.
- ✗
ROC-AUC
Why it's wrong here
ROC-AUC can be optimistic for imbalanced datasets.
- ✓
Precision-Recall curve
Why this is correct
Precision-Recall curve focuses on the positive class, suitable for imbalanced data.
Quick reference
Asymmetric Encryption Algorithm Comparison
| Algorithm | Key Exchange | Signatures | Equivalent Security Key | Notes |
|---|---|---|---|---|
| RSA-3072 | Yes | Yes | 128-bit | Widely deployed; slow for bulk data |
| ECDSA P-256 | No | Yes | 128-bit | Fast signatures; standard TLS certs |
| ECDH / ECDHE | Yes | No | 128-bit | Perfect forward secrecy in TLS 1.3 |
| DH / DHE | Yes | No | 128-bit (3072-bit key) | Replaced by ECDHE in modern TLS |
| Ed25519 | No | Yes | ~128-bit | SSH keys, modern PKI |
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Last reviewed: Jun 20, 2026
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