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

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SASInstitute A00-406 Exam Syllabus Topics:

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

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

A) The past behavior or preferences of users
B) Item-based clustering
C) The characteristics of the items being recommended
D) The popularity of items

2. Which of the following best describes unstructured data?

A) Data with a clear schema
B) Data that is difficult to process and lacks a predefined structure
C) Data that is organized in rows and columns
D) Data stored in a relational database

3. Which statement is true regarding decision trees and models based on ensembles of trees?

A) In the gradient boosting algorithm, for all but the first iteration, the target is the residual from the previous decision tree model.
B) For a Forest model, the out-of-bag sample is simply the original validation data set from when the raw data partitioning took place.
C) In the Forest algorithm, each individual tree is pruned based on using minimum Average Squared Error.
D) A single decision tree will always be outperformed by a model based on an ensemble of trees.

4. What is the main advantage of ensemble learning methods, such as Random Forest, in a machine learning pipeline?

A) They require minimal data preprocessing.
B) They combine multiple models to improve predictive performance.
C) They are not suitable for large datasets.
D) They are simple and easy to interpret.

5. Which SAS Viya component is typically used for deploying and monitoring machine learning models in production?

A) SAS Data Loader
B) SAS Enterprise Miner
C) SAS Visual Analytics
D) SAS Model Manager

Solutions: