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

1. What is the primary role of a loss function in model training?

A) To visualize the data
B) To measure the difference between predicted and actual values
C) To maximize the model's performance
D) To assess the accuracy of the model

2. What is the purpose of hyperparameter tuning in a machine learning pipeline?

A) To train the model
B) To evaluate the model's predictions
C) To select the most important features
D) To optimize the model's hyperparameters for better performance

3. In a machine learning pipeline, what is the purpose of cross-validation?

A) To evaluate the model's performance on new data
B) To visualize the data distribution
C) To split the dataset into training and testing sets
D) To train multiple models on different subsets of the data to assess generalization

4. In the context of model deployment, what is "model compliance"?

A) The process of feature selection
B) The model's efficiency
C) The model's simplicity
D) The degree to which the model adheres to regulatory or ethical guidelines

5. What does the term "bagging" refer to in ensemble learning?

A) A technique that reduces model complexity
B) The process of combining multiple identical models to reduce variance
C) A form of dimensionality reduction
D) A type of feature extraction

Solutions: