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Exam AI-102 topic 2 question 11 discussion

Actual exam question from Microsoft's AI-102
Question #: 11
Topic #: 2
[All AI-102 Questions]

You use the Custom Vision service to build a classifier.
After training is complete, you need to evaluate the classifier.
Which two metrics are available for review? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

  • A. recall
  • B. F-score
  • C. weighted accuracy
  • D. precision
  • E. area under the curve (AUC)
Show Suggested Answer Hide Answer
Suggested Answer: AD 🗳️

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zellck
Highly Voted 1 year, 5 months ago
Selected Answer: AD
AD is the answer. https://learn.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/getting-started-build-a-classifier#evaluate-the-classifier After training has completed, the model's performance is estimated and displayed. The Custom Vision Service uses the images that you submitted for training to calculate precision and recall. Precision and recall are two different measurements of the effectiveness of a classifier: - Precision indicates the fraction of identified classifications that were correct. For example, if the model identified 100 images as dogs, and 99 of them were actually of dogs, then the precision would be 99%. - Recall indicates the fraction of actual classifications that were correctly identified. For example, if there were actually 100 images of apples, and the model identified 80 as apples, the recall would be 80%.
upvoted 5 times
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HaraTadahisa
Most Recent 5 months, 3 weeks ago
Selected Answer: AD
I say this answer is A and D.
upvoted 1 times
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anto69
6 months ago
Selected Answer: AD
Chat GPT and me: A + D
upvoted 1 times
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hatanaoki
6 months, 2 weeks ago
A and D are right answer.
upvoted 1 times
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evangelist
9 months, 4 weeks ago
Selected Answer: AD
Zellck provided an excellent answer with precise documentation and interpretation of precision and recall metrics. Precision refers to the positive predictive value - the proportion of true positive results among all positively identified outcomes. Meanwhile, recall represents sensitivity - the proportion of actual positive cases that are correctly identified as such. Precision and recall form a fundamental pair of performance indicators that entail an inherent trade-off. As one metric is optimized, the other typically suffers as a consequence. Specifically, as the precision rate increases, the recall rate often correspondingly decreases. The optimal balance between precision and recall depends on the business context and specific needs of the use case. By clearly explaining the definitions and relationship between these two metrics, Zellck thoroughly addressed the concepts with clarity and accuracy.
upvoted 2 times
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rdemontis
1 year, 1 month ago
Selected Answer: AD
Answer is correct https://learn.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/getting-started-build-a-classifier#evaluate-the-classifier
upvoted 1 times
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trashbox
1 year, 1 month ago
Appeared on Oct/29/2023.
upvoted 4 times
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zellck
1 year, 5 months ago
Same as Question 2. https://www.examtopics.com/discussions/microsoft/view/55211-exam-ai-102-topic-2-question-2-discussion
upvoted 1 times
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halfway
2 years ago
Selected Answer: AD
Precision and Recall: https://learn.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/getting-started-build-a-classifier#evaluate-the-classifier
upvoted 1 times
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Eltooth
2 years, 4 months ago
Selected Answer: AD
A and D are correct answers - as per PHD_CHENG https://docs.microsoft.com/en-us/learn/modules/cv-classify-bird-species/4-understand-results-test
upvoted 2 times
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PHD_CHENG
2 years, 6 months ago
Was on exam 7 Jun 2022
upvoted 1 times
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PHD_CHENG
2 years, 7 months ago
Selected Answer: AD
Answer is correct. You can find the metrics from Microsoft link https://docs.microsoft.com/en-us/learn/modules/cv-classify-bird-species/4-understand-results-test
upvoted 4 times
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