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SASInstitute A00-406 Exam Syllabus Topics:

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

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

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

3. What is the primary goal of hyperparameter tuning during model building?

A) To increase model complexity
B) To optimize the settings that control the model's learning process
C) To improve data preprocessing techniques
D) To add more features to the model

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

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

5. When deploying a model, what is "model explainability"?

A) The simplicity of the model
B) The process of data preprocessing
C) The capability to interpret and understand the model's decisions and predictions
D) The time it takes to make predictions

Solutions: