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SASInstitute A00-406 Exam Syllabus Topics:

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

1. In the context of model building, what is the purpose of hyperparameter tuning?

A) Selecting the most important features
B) Visualizing data
C) Optimizing the model's hyperparameters for better performance
D) Training the model

2. What does the term "bias" in machine learning refer to?

A) A model's inability to generalize to new data
B) Systematic errors that cause a model to consistently underpredict or overpredict
C) The overall accuracy of a model
D) The simplicity of a model

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

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

4. 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) Classification predicts categorical outcomes, while regression predicts numeric outcomes.
D) Regression predicts categorical outcomes, while classification predicts numeric outcomes.

5. What is the primary goal of building models in data science and machine learning?

A) Feature engineering
B) Data visualization
C) Making predictions or inferences from data
D) Data cleaning

Solutions: