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

1. What is "model retraining" in the context of model deployment?

A) The process of data preprocessing
B) The process of building the initial model
C) The process of feature selection
D) Periodically updating and improving a deployed model with new data

2. What is the primary purpose of "continuous integration and continuous deployment" (CI/CD) in the context of model deployment?

A) To visualize data distribution
B) To create synthetic data
C) To evaluate the model's accuracy
D) To automate the testing, integration, and deployment of new model versions

3. Which type of model is well-suited for solving classification problems when dealing with high- dimensional data, such as text?

A) Support Vector Machine (SVM)
B) Linear Regression
C) K-Means Clustering
D) Random Forest

4. What is the main advantage of ensemble methods in model building?

A) They produce simple and interpretable models
B) They combine multiple models to improve predictive performance
C) They work well with high-dimensional data
D) They require minimal data preprocessing

5. Which algorithm is commonly used for binary classification in machine learning pipelines, especially when dealing with imbalanced datasets?

A) Principal Component Analysis (PCA)
B) Support Vector Machine (SVM)
C) Linear Regression
D) K-Means Clustering

Solutions: