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SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions:

1. What does "feature selection" refer to in the context of model building?

A) The process of choosing the most relevant variables (features) for the model
B) The creation of synthetic features from existing data
C) The evaluation of model accuracy
D) The visualization of data distribution

2. What is "model retraining" in the context of model deployment?

A) Periodically updating and improving a deployed model with new data
B) The process of feature selection
C) The process of data preprocessing
D) The process of building the initial model

3. What is the primary purpose of model deployment in the context of data science and machine learning?

A) Data preprocessing
B) Making the model available for use in real-world applications
C) Model evaluation
D) Model building

4. What is feature engineering in the context of machine learning pipelines?

A) Testing the model's performance
B) Building a machine learning model from scratch
C) Creating new features from existing data
D) Applying the model to new data

5. In the context of data integration, what does "data transformation" refer to?

A) Extracting data from source systems
B) Storing data in a centralized repository
C) Backing up data for disaster recovery
D) Converting and reshaping data to match the target schema

Solutions: