SASInstitute A00-406 Actual Free Exam Questions & Community Discussion

Exam Code/Number: A00-406
Exam Name/Title: SAS® Viya® Supervised Machine Learning Pipelines
Certification Provider: SASInstitute
Corresponding Certification: SAS Certified Specialist

Exam Questions: 98
Updated On: Jul 05, 2026

Question #1

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

A. To execute data queries

B. To optimize data storage

C. To create data visualizations

D. To assess the quality and characteristics of data

Discussion 0

Correct Answer: D Vote an answer

Question #2

Which technique is commonly used for feature scaling or normalization in machine learning pipelines?

A. One-Hot Encoding

B. Principal Component Analysis (PCA)

C. Decision Trees

D. Standardization

Discussion 0

Correct Answer: D Vote an answer

Question #3

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

A. A model that performs well on new, unseen data

B. A model that is undertrained and has high bias

C. A model that is unable to make predictions

D. A model that has too much complexity and fits the training data too closely

Discussion 0

Correct Answer: D Vote an answer

Question #4

When building a recommendation system, what does "collaborative filtering" rely on?

A. The popularity of items

B. The characteristics of the items being recommended

C. Item-based clustering

D. The past behavior or preferences of users

Discussion 0

Correct Answer: D Vote an answer

Question #5

Which of the following best describes unstructured data?

A. Data with a clear schema

B. Data that is organized in rows and columns

C. Data stored in a relational database

D. Data that is difficult to process and lacks a predefined structure

Discussion 0

Correct Answer: D Vote an answer

Question #6

What is the primary goal of hyperparameter tuning during model building?

A. To improve data preprocessing techniques

B. To optimize the settings that control the model's learning process

C. To add more features to the model

D. To increase model complexity

Discussion 0

Correct Answer: B Vote an answer

Question #7

What is the difference between a classification problem and a regression problem in machine learning?

A. Classification is a type of regression problem.

B. Regression predicts categorical outcomes, while classification predicts numeric outcomes.

C. There is no difference; the terms are used interchangeably.

D. Classification predicts categorical outcomes, while regression predicts numeric outcomes.

Discussion 0

Correct Answer: D Vote an answer

Question #8

When deploying a machine learning model, what is meant by "model latency"?

A. The time it takes to build a model

B. The time it takes to train a model

C. The time it takes to create synthetic data

D. The time it takes for the model to make predictions once deployed

Discussion 0

Correct Answer: D Vote an answer

Question #9

What does the term "bagging" refer to in ensemble learning?

A. The process of combining multiple identical models to reduce variance

B. A form of dimensionality reduction

C. A technique that reduces model complexity

D. A type of feature extraction

Discussion 0

Correct Answer: A Vote an answer

Question #10

What is the primary function of a data catalog in managing data sources?

A. Data storage

B. Data analysis

C. Data documentation and discovery

D. Data visualization

Discussion 0

Correct Answer: C Vote an answer

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