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

A00-406

Exam Code: A00-406

Exam Name: SAS® Viya® Supervised Machine Learning Pipelines

Updated: Sep 15, 2026

Q & A: 98 Questions and Answers

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SASInstitute A00-406 Exam Syllabus Topics:
SectionObjectives
Model Evaluation and Deployment- Model deployment
  • 1. Scoring models in SAS Viya
    • 2. Model governance
      - Model assessment metrics
      • 1. ROC and lift charts
        • 2. Accuracy, precision, recall
          Supervised Machine Learning Models- Model selection techniques
          • 1. Cross-validation
            • 2. Performance comparison
              - Regression and classification models
              • 1. Linear and logistic regression
                • 2. Tree-based models
                  Data Preparation for Machine Learning- Data cleaning and preprocessing
                  • 1. Handling missing values
                    • 2. Outlier detection and treatment
                      - Feature engineering
                      • 1. Variable transformation
                        • 2. Encoding categorical variables
                          Machine Learning Pipelines in SAS Viya- Model tuning and optimization
                          • 1. Hyperparameter tuning
                            • 2. Automated machine learning (AutoML)
                              - Pipeline construction
                              • 1. Node-based pipeline design
                                • 2. Model Studio workflows
                                  SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions:

                                  Question #1
                                  What is the significance of the "bias-variance trade-off" in machine learning?

                                  A. It indicates the trade-off between accuracy and precision.
                                  B. It is not relevant in machine learning.
                                  C. It represents the trade-off between underfitting and overfitting.
                                  D. It refers to the trade-off between the number of features and the model's complexity.


                                  Question #2
                                  Which data source typically provides access to real-time financial market data?

                                  A. Weather stations
                                  B. Online news websites
                                  C. Stock market APIs
                                  D. Social media platforms


                                  Question #3
                                  Refer to the treemap shown in the exhibit below:

                                  Which statement is true about the tree map for a decision tree with a binary target?

                                  A. The top bar represents the node with the highest probability of event.
                                  B. The top bar represents the node with the highest count.
                                  C. The darker bars represent nodes with a lower probability of event.
                                  D. The wider bars represent nodes with a higher probability of event.


                                  Question #4
                                  What is the purpose of regularization techniques in model building, such as L1 and L2 regularization?

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


                                  Question #5
                                  In the context of data sources, what is meant by data versioning?

                                  A. Compressing data to reduce storage space
                                  B. Keeping track of different versions or changes to data over time
                                  C. Encrypting data to protect against unauthorized access
                                  D. Storing multiple copies of the same data to increase redundancy


                                  Solutions:

                                  Question #1
                                  Correct Answer: C
                                  Question #2
                                  Correct Answer: C
                                  Question #3
                                  Correct Answer: B
                                  Question #4
                                  Correct Answer: C
                                  Question #5
                                  Correct Answer: B

                                  Related Certifications
                                  SAS Institute Systems
                                  SAS Visual Business Analytics Specialist
                                  Programming Fundamentals
                                  SAS Certified Specialist
                                  SAS Foundation
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