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

1. What is metadata in the context of data sources?

A) Data that is encrypted for security
B) Data that is in a non-standard, proprietary format
C) Data that is stored in a physical format
D) Data about data, providing information such as data source, structure, and context

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

A) Standardization
B) One-Hot Encoding
C) Principal Component Analysis (PCA)
D) Decision Trees

3. Which hyperparameter in a decision tree model controls the depth of the tree and helps prevent overfitting?

A) Max features
B) Min samples split
C) Learning rate
D) Max depth

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

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

5. Which of the following is NOT a common data format for exchanging data between systems?

A) CSV (Comma-Separated Values)
B) SQL (Structured Query Language)
C) JSON (JavaScript Object Notation)
D) HTML (Hypertext Markup Language)

Solutions: