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SASInstitute A00-406 Exam Syllabus Topics:

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

1. What is the purpose of data profiling in data source management?

A) To execute data queries
B) To create data visualizations
C) To assess the quality and characteristics of data
D) To optimize data storage

2. Which evaluation metric is commonly used for assessing the performance of a regression model?

A) Confusion Matrix
B) F1 Score
C) Mean Absolute Error (MAE)
D) Precision

3. What is overfitting in machine learning, and how can it be addressed in a pipeline?

A) Overfitting is not a concern in machine learning pipelines.
B) Overfitting occurs when the model fits the training data too closely and may not generalize well. It can be addressed by regularization techniques.
C) Overfitting occurs when the model is too complex and overperforms.
D) Overfitting occurs when the model is too simple and underperforms.

4. What does "data lineage" refer to in the context of data source management?

A) The structure of a relational database
B) The security protocols for data access
C) The physical location of data storage
D) The history of data transformation processes

5. What is "model reevaluation" in the model deployment phase?

A) The evaluation of data distribution
B) The process of data preprocessing
C) The process of selecting features
D) The periodic assessment of a deployed model's performance and potential retraining

Solutions: