Microsoft Certified Azure AI Engineer Associate - AI-102
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You have developed a language understanding model for a virtual assistant that can handle various intents such as 'book_flight', 'check_weather', and 'play_music'. You want to test the model's performance using a set of test data. Which of the following approaches should you use to evaluate the model's accuracy?
You have developed a language understanding model for a virtual assistant that can handle various intents such as 'book_flight', 'check_weather', and 'play_music'. You want to test the model's performance using a set of test data. Which of the following approaches should you use to evaluate the model's accuracy?
Explanation:
Measuring the model's performance using a combination of precision, recall, and F1-score metrics provides a more comprehensive evaluation of its accuracy. Precision measures the proportion of correct predictions among all positive predictions, recall measures the proportion of correct predictions among all actual positive samples, and F1-score is the harmonic mean of precision and recall. This approach allows you to identify the strengths and weaknesses of the model and make targeted improvements. Options A, B, and C do not provide a complete assessment of the model's performance.