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

1. When assessing a classification model, what is the confusion matrix used to measure?

A) Model complexity
B) Precision and recall
C) Data distribution
D) Model accuracy

2. Which technique is used for feature selection in a machine learning pipeline when dealing with a large number of features?

A) Regularization
B) Naive Bayes
C) One-Hot Encoding
D) Principal Component Analysis (PCA)

3. What is the purpose of a confusion matrix in the context of classification models?

A) To evaluate model performance, especially for binary classification
B) To visualize the data
C) To compute the mean squared error
D) To summarize the distribution of target variables

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

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

5. Which evaluation metric is commonly used for assessing the performance of a regression model?

A) Confusion Matrix
B) F1 Score
C) Precision
D) Mean Absolute Error (MAE)

Solutions: