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Exam Code: A00-406
Exam Name: SAS® Viya® Supervised Machine Learning Pipelines
Updated: Oct 07, 2026
Q & A: 98 Questions and Answers
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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Model Assessment and Deployment | 24-30% | - Assessing model performance (metrics, ROC curves, confusion matrices) - Deploying models into production |
| Topic 2: Data Sources | 30-36% | - Dimensionality reduction and feature engineering - Exploring and modifying data - Importing and preparing data |
| Topic 3: Building Models | 40-46% | - Supervised model creation (decision trees, ensembles, SVM, neural networks) - Model comparison and selection |
What is the primary role of a loss function in model training?
Correct Answer: B 🗳️
What is the main goal of data preprocessing in a machine learning pipeline?
Correct Answer: D 🗳️
Which machine learning technique is typically used for building a model to predict a numeric target variable?
Correct Answer: A 🗳️
In the context of model assessment, what does "bias" refer to?
Correct Answer: D 🗳️
What is the primary role of a data warehouse in an organization?
Correct Answer: B 🗳️
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