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AI-900: Custom Vision Model Metrics Understanding Precision, Recall, AP

Learn how Precision, Recall, and AP metrics contribute to assessing the performance of your Custom Vision models, ensuring a comprehensive evaluation for accuracy and relevance.

Table of Contents

Question

What are the three metrics that help for evaluate Custom vision model performance?

Answer

Recall, Average Precision (AP), Precision

Explanation

Custom vision is one of the Computer Vision tasks. Custom vision service helps create your own computer vision model. There are three main performance metrics for the Custom vision models: Precision, Recall, and Average Precision (AP).

Precision defines the percentage of the class predictions that the model makes correct. For example, if the model predicts that ten images are bananas, and there are actually only seven bananas, the model precision is 70%.

Recall defines the percentage of the class identification that the model makes correct. For example, if there are ten apple images, and the model identifies only eight, the model recall is 80%.

Average Precision (AP) is the combined metrics of both Precision and Recall.

Accuracy is a Classification model metric, but it is not used for Custom vision models performance assessments.

Number of Points is a Clustering model metric and is not used for Custom vision models performance assessments.

Mean Absolute Error (MAE) is a Regression model metric and is not used for Custom vision models performance assessments.

Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Fundamentals AI-900 exam and earn Microsoft Azure AI Fundamentals AI-900 certification.

Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump

Alex Lim is a certified IT Technical Support Architect with over 15 years of experience in designing, implementing, and troubleshooting complex IT systems and networks. He has worked for leading IT companies, such as Microsoft, IBM, and Cisco, providing technical support and solutions to clients across various industries and sectors. Alex has a bachelor’s degree in computer science from the National University of Singapore and a master’s degree in information security from the Massachusetts Institute of Technology. He is also the author of several best-selling books on IT technical support, such as The IT Technical Support Handbook and Troubleshooting IT Systems and Networks. Alex lives in Bandar, Johore, Malaysia with his wife and two chilrdren. You can reach him at [email protected] or follow him on Website | Twitter | Facebook

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