SASInstitute A00-406 Questions & Answers - in .pdf
- Total Q&A: 98
- Update: Oct 06, 2026
- Price: $59.99
- Vendor: SASInstitute
- Exam Code: A00-406
- Exam Name: SAS® Viya® Supervised Machine Learning Pipelines
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SASInstitute A00-406 Q&A - Testing Engine
- Total Q&A: 98
- Update: Oct 06, 2026
- Price: $59.99
- Vendor: SASInstitute
- Exam Code: A00-406
- Exam Name: SAS® Viya® Supervised Machine Learning Pipelines
- Features:
- Uses the World Class A00-406 Testing Engine.
- Real A00-406 exam questions with answers.
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SASInstitute A00-406 Exam Syllabus Topics:
| Section | Objectives |
|---|
| Topic 1: Model Evaluation and Deployment | - Model assessment metrics
- 1. ROC and lift charts
- 2. Accuracy, precision, recall
- Model deployment
- 1. Scoring models in SAS Viya
- 2. Model governance
|
| Topic 2: Supervised Machine Learning Models | - Model selection techniques
- 1. Cross-validation
- 2. Performance comparison
- Regression and classification models
- 1. Tree-based models
- 2. Linear and logistic regression
|
| Topic 3: Data Preparation for Machine Learning | - Feature engineering
- 1. Variable transformation
- 2. Encoding categorical variables
- Data cleaning and preprocessing
- 1. Outlier detection and treatment
- 2. Handling missing values
|
| Topic 4: Machine Learning Pipelines in SAS Viya | - Model tuning and optimization
- 1. Hyperparameter tuning
- 2. Automated machine learning (AutoML)
- Pipeline construction
- 1. Model Studio workflows
- 2. Node-based pipeline design
|
SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions:
Question #1
Which hyperparameter in a decision tree model controls the depth of the tree and helps prevent overfitting?
A. Min samples split
B. Learning rate
C. Max depth
D. Max features
Question #2
Which of the following is a common source for external data in the context of business analytics?
A. CRM data
B. Intranet databases
C. Company financial reports
D. Employee records
Question #3
What is "model reevaluation" in the model deployment phase?
A. The process of selecting features
B. The periodic assessment of a deployed model's performance and potential retraining
C. The process of data preprocessing
D. The evaluation of data distribution
Question #4
In the context of data sources, what is ETL?
A. Extract, Transform, Load
B. Efficient Text Link
C. Execute, Terminate, Launch
D. Examine, Test, Log
Question #5
In the context of model building, what is the purpose of hyperparameter tuning?
A. Optimizing the model's hyperparameters for better performance
B. Training the model
C. Visualizing data
D. Selecting the most important features
Solutions:
Question #1
Correct Answer: C | Question #2
Correct Answer: C | Question #3
Correct Answer: B | Question #4
Correct Answer: A | Question #5
Correct Answer: A |
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