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

1. Which hyperparameter in a decision tree model controls the depth of the tree and helps prevent overfitting?

A) Max depth
B) Learning rate
C) Min samples split
D) Max features

2. Which of the following metrics is commonly used to evaluate the performance of a binary classification model in a machine learning pipeline?

A) Accuracy
B) R-squared
C) Mean Absolute Error (MAE)
D) Root Mean Squared Error (RMSE)

3. What is the primary objective of model evaluation in the context of building predictive models?

A) Discovering patterns in data
B) Visualizing data
C) Cleaning the data
D) Assessing the model's performance and accuracy

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

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

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

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

Solutions: