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SASInstitute A00-406 Exam Syllabus Topics:

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

1. Which technique is used for feature selection in a machine learning pipeline when dealing with a large number of features?

A) One-Hot Encoding
B) Naive Bayes
C) Principal Component Analysis (PCA)
D) Regularization

2. In a machine learning pipeline, what is the purpose of cross-validation?

A) To split the dataset into training and testing sets
B) To visualize the data distribution
C) To evaluate the model's performance on new data
D) To train multiple models on different subsets of the data to assess generalization

3. What is the primary objective of model evaluation in the context of building predictive models?

A) Discovering patterns in data
B) Visualizing data
C) Assessing the model's performance and accuracy
D) Cleaning the data

4. Which of the following is an example of a NoSQL database that is commonly used to store unstructured data?

A) Microsoft SQL Server
B) MySQL
C) MongoDB
D) Oracle Database

5. What is the main purpose of feature engineering in model building?

A) Data preprocessing
B) Creating new features or transforming existing ones to improve model performance
C) Data visualization
D) Model evaluation

Solutions: