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

1. What is the difference between a classification problem and a regression problem in machine learning?

A) Classification is a type of regression problem.
B) Classification predicts categorical outcomes, while regression predicts numeric outcomes.
C) There is no difference; the terms are used interchangeably.
D) Regression predicts categorical outcomes, while classification predicts numeric outcomes.

2. Which machine learning technique is typically used for building a model to predict a numeric target variable?

A) Regression
B) Clustering
C) Classification
D) Dimensionality reduction

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

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

4. What is feature engineering in the context of machine learning pipelines?

A) Applying the model to new data
B) Creating new features from existing data
C) Testing the model's performance
D) Building a machine learning model from scratch

5. What is the main purpose of feature engineering in model building?

A) Data visualization
B) Model evaluation
C) Data preprocessing
D) Creating new features or transforming existing ones to improve model performance

Solutions: