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SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions (Q37-Q42):

NEW QUESTION # 37
In machine learning, what does "overfitting" refer to?

A. A model that is unable to make predictions
B. A model that has too much complexity and fits the training data too closely
C. A model that performs well on new, unseen data
D. A model that is undertrained and has high bias

Answer: B

NEW QUESTION # 38
Which of the following is a common source for external data in the context of business analytics?

A. Intranet databases
B. Employee records
C. Company financial reports
D. CRM data

Answer: C

NEW QUESTION # 39
In natural language processing, what does "stemming" involve?

A. Converting text to numbers for model input
B. Grouping similar words together based on their meanings
C. Creating new words to improve model performance
D. Reducing words to their base or root form

Answer: D

NEW QUESTION # 40
What is the purpose of regularization techniques in model building, such as L1 and L2 regularization?

A. To increase model complexity
B. To prevent overfitting and reduce model complexity
C. To speed up model training
D. To add more features to the model

Answer: B

NEW QUESTION # 41
What is the primary goal of A/B testing in the context of model deployment?

A. To evaluate the model's accuracy
B. To create synthetic data
C. To assess data quality
D. To compare two different versions of a model or strategy to determine which performs better

Answer: D

NEW QUESTION # 42
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