You create a new LUIS application in the LUIS portal by providing the values for name, language, description and prediction resource. You populate the domain with intents, entities and utterances. Next, you train your application, create a prediction resource and publish the application to an endpoint URL. While you query the endpoint URL for various utterances, you find the top intent and next intent scores are close enough. You also find a few utterances that are not predicted for the labeled intent. 
Given the scenario above, what are the three options you would use to improve the prediction accuracy?

Answer options:

A.Review dashboard colors and find intents with incorrect/unclear predictions.
B.Enable active learning, capture endpoint queries and relabel entities.
C.Set endpoint query parameter log=false, capture endpoint queries and relabel entities.
D.Add example utterances as pattern, train and publish application again.
E.Add more example utterances to improve prediction score. 

Correct Answers: A, B and D
Option A is correct. You can review dashboard analysis to find unclear predictions marked with Orange color and incorrect predictions marked with Red color.
Option B is correct. You can log user queries by enabling active learning, reviewing the utterances with lower prediction scores and review/modify the intents and entities to improve the model accuracy.
Option C is incorrect because the value of the endpoint query parameter log has to be maintained as true to log user queries.
Option D is correct. In the LUIS portal, you can use a pattern to improve prediction accuracy for utterances.
Option E is incorrect because adding more example utterances would not fix the utterances with incorrect or unclear predictions.
References:
To learn more about improving the prediction accuracy of a LUIS application, use the links given below: 

https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-how-to-use-dashboard
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-how-to-review-endpoint-utterances
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-how-to-model-intent-pattern