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

1. What is the main goal of data preprocessing in a machine learning pipeline?

A) To prepare the data for analysis and modeling
B) To train the model
C) To remove irrelevant features
D) To visualize the data

2. 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

3. What is a data lake architecture designed to store primarily?

A) All types of data, including structured and unstructured data
B) Data from a single source or department
C) Highly structured data in tabular format
D) Only unstructured data in raw form

4. Which type of model is typically used for time-series forecasting?

A) Decision Trees
B) AutoRegressive Integrated Moving Average (ARIMA)
C) Logistic Regression
D) K-Means Clustering

5. What does "feature selection" refer to in the context of model building?

A) The evaluation of model accuracy
B) The creation of synthetic features from existing data
C) The process of choosing the most relevant variables (features) for the model
D) The visualization of data distribution

Solutions: