Exam AI-102 topic 2 question 11 discussion

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%.

A. recall D. precision

recall measures the ability of the classifier to find all the relevant instances in the dataset. It is a key metric for evaluating the effectiveness of a classifier in identifying relevant items. precision measures the ability of the classifier to correctly identify only the relevant instances in the dataset. It is important for evaluating how many of the predicted positive instances are actually relevant. AD are the answers

I say this answer is A and D.

Chat GPT and me: A + D

A and D are right answer.

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.

Answer is correct https://learn.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/getting-started-build-a-classifier#evaluate-the-classifier

Appeared on Oct/29/2023.

Same as Question 2. https://www.examtopics.com/discussions/microsoft/view/55211-exam-ai-102-topic-2-question-2-discussion

Precision and Recall: https://learn.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/getting-started-build-a-classifier#evaluate-the-classifier

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

Was on exam 7 Jun 2022

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