You provision a LUIS service in Azure and use Machine Learning features to identify new items for a concept or a distinguishing trait. For example add new medical terms to a subject domain. What are the two types of features that are supported as part of schema design?

Answer options:

A.Patterns
B.Phrase list
C.Model
D.Prediction

Correct Answers: B and C
Option A is incorrect because patterns are used to help improve prediction accuracy. You can reduce the number of utterances while improving the overall accuracy. Example of pattern utterance is “Who does {EmployeeListEntity} report to[?]”
Option B is correct because the phrase list as a feature is supported. They act as domain specific vocabulary and enhance the quality of intents and entities. Examples of phrase lists are Airport Codes and Medical terms.
Option C is correct because Model (intent and entity) as a feature is supported. You can add an entity as a feature if that entity is significant for the intent. Likewise you can add an entity as a feature to another entity if it enhances prediction of that entity.
Option D is incorrect because Prediction is not a supported feature.
Reference:
To learn more about use of features in a LUIS application, use the link given below: 

https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-concept-feature