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SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions (Q19-Q24):

NEW QUESTION # 19
Which algorithm is commonly used for binary classification in machine learning pipelines, especially when dealing with imbalanced datasets?

A. Linear Regression
B. Principal Component Analysis (PCA)
C. Support Vector Machine (SVM)
D. K-Means Clustering

Answer: C

NEW QUESTION # 20
What is the main purpose of feature engineering in model building?

A. Model evaluation
B. Data visualization
C. Creating new features or transforming existing ones to improve model performance
D. Data preprocessing

Answer: C

NEW QUESTION # 21
Which statements are true for the F1 score?
(Choose 2.)

A. F1 score is applicable to a model with an interval target.
B. F1 score is calculated based on a depth value.
C. F1 score is calculated based on a cut off value.
D. F1 score is applicable to a model with a binary target.

Answer: C,D

NEW QUESTION # 22
What is the primary purpose of model deployment in the context of data science and machine learning?

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

Answer: C

NEW QUESTION # 23
Which data source allows for real-time data streaming and processing?

A. Cloud storage
B. Static data files
C. IoT devices
D. Data warehouses

Answer: C

NEW QUESTION # 24
......

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Study A00-406 Material - A00-406 Book Free

A00-406 Book Free & A00-406 Valid Real Test

SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions (Q19-Q24):

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