You are training a Language Understanding model for a user support system. You create the first intent named GetContactDetails and add 200 examples. You need to decrease the likelihood of a false positive. What should you do?

QuestionsCategory: AI-102You are training a Language Understanding model for a user support system. You create the first intent named GetContactDetails and add 200 examples. You need to decrease the likelihood of a false positive. What should you do?
Admin Staff asked 3 months ago
You are training a Language Understanding model for a user support system.
You create the first intent named GetContactDetails and add 200 examples.
You need to decrease the likelihood of a false positive.
What should you do?

A. Enable active learning.

B. Add a machine learned entity.

C. Add additional examples to the GetContactDetails intent.

D. Add examples to the None intent.








 

Suggested Answer: A

Active learning is a technique of machine learning in which the machine learned model is used to identify informative new examples to label. In LUIS, active learning refers to adding utterances from the endpoint traffic whose current predictions are unclear to improve your model.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-glossary

This question is in AI-102 Designing and Implementing an Azure AI Solution Exam
For getting Microsoft Certified: Azure AI Engineer Associate Certificate




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