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

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

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

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

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

3. In model assessment, what does "cross-validation" aim to address?

A) Model deployment
B) Data preprocessing
C) Overfitting and generalization
D) Training a model

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

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

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

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

Solutions: