AI-900Domain 2: Describe Fundamental Principles of Machine Learning on AzureMachine Learning PrincipleshardSingle choice
A fraud classifier flags 90 of 100 real frauds (90 true positives) but also flags 40 legitimate transactions (40 false positives). What are its recall and precision?
A.Recall 69%, precision 90%
The metrics are swapped — recall comes out to 90% here.
B.Recall 90%, precision ~69%
Recall 90%, precision 69%. Correct.
C.Both are 90%
Precision is diluted by the 40 false positives.
D.Recall ~69%, precision 90%
Recall is the 90% figure — precision drops to ~69%.
Why this answer
Recall = TP/(TP+FN) = 90/100 = 90% (of actual frauds, how many caught). Precision = TP/(TP+FP) = 90/130 ≈ 69% (of flagged items, how many were real). Exam tip: recall answers 'of the real positives'; precision answers 'of my positive predictions'.
Correct answer: B · Last reviewed 2026-02-14
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