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

1. What is the main advantage of ensemble learning methods, such as Random Forest, in a machine learning pipeline?

A) They are simple and easy to interpret.
B) They require minimal data preprocessing.
C) They are not suitable for large datasets.
D) They combine multiple models to improve predictive performance.

2. In model evaluation, what is the purpose of a ROC curve (Receiver Operating Characteristic)?

A) To measure feature importance
B) To visualize data distribution
C) To compare models' performance in terms of sensitivity and specificity
D) To evaluate the mean squared error of a model

3. When deploying a machine learning model, what is meant by "model latency"?

A) The time it takes to build a model
B) The time it takes to train a model
C) The time it takes for the model to make predictions once deployed
D) The time it takes to create synthetic data

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

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

5. What is the primary purpose of model deployment in the context of data science and machine learning?

A) Making the model available for use in real-world applications
B) Model evaluation
C) Model building
D) Data preprocessing

Solutions: