Exam AI-102 Topic 5 Question 364 Discussion

Explanation:
The percentage of false positives is [0].
The value for the number of true positives divided by the total number of true positives and false negatives is [100].
The screenshot shows the Performance tab of a Custom Vision object detection model after training.
Two key performance metrics are in focus:
False Positives (FP):
False positives occur when the model incorrectly predicts an object that isn't present.
In the provided exhibit, the model shows 0% false positives.
This means it did not incorrectly classify any non-object as an object.
Recall (True Positives ÷ (True Positives + False Negatives)):
This measures how many of the actual objects were correctly detected.
Formula: Recall = TP / (TP + FN).
In the performance report, recall is 100%, meaning the model correctly detected all the actual objects (no false negatives).
Evaluating the answer choices:
False positives: 0%
Recall (TP ÷ (TP + FN)): 100%
Correct Answers:
False positives # 0
Recall # 100
Microsoft References
Custom Vision performance metrics
Precision, recall, and accuracy in machine learning