SASInstitute SAS® Viya® Supervised Machine Learning Pipelines : A00-406

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SASInstitute A00-406 Exam Syllabus Topics:

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

1. What is the primary objective of model validation during the model assessment phase?

A) To assess the accuracy of the model
B) To ensure the model generalizes well to new, unseen data
C) To create synthetic data
D) To build a model from scratch

2. Which data source allows for real-time data streaming and processing?

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

3. What is the primary purpose of model documentation in the model deployment phase?

A) To provide information on the model's development, architecture, and usage
B) To assess data quality
C) To evaluate the model's accuracy
D) To create synthetic data

4. A project has been created and a pipeline has been run in Model Studio.
Which project setting can you edit?

A) Rules for model comparison statistic
B) Advisor Options for missing values
C) Event-based Sampling proportions
D) Partition Data percentages

5. In machine learning, what does "overfitting" refer to?

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

Solutions: