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

1. What is the purpose of cross-validation in model building and evaluation?

A) Assessing the model's generalization performance
B) Splitting the dataset into training and testing sets
C) Reducing the dataset size
D) Generating synthetic data

2. What is the purpose of regularization techniques in model building, such as L1 and L2 regularization?

A) To speed up model training
B) To prevent overfitting and reduce model complexity
C) To increase model complexity
D) To add more features to the model

3. 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) Model evaluation
D) Data visualization

4. What does the term "bias" in machine learning refer to?

A) The simplicity of a model
B) Systematic errors that cause a model to consistently underpredict or overpredict
C) The overall accuracy of a model
D) A model's inability to generalize to new data

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

A) To optimize data storage
B) To execute data queries
C) To assess the quality and characteristics of data
D) To create data visualizations

Solutions: