SASInstitute A00-406

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SASInstitute A00-406 Exam Syllabus Topics:

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) Min samples split
C) Learning rate
D) Max features

2. What is the main advantage of ensemble methods in model building?

A) They produce simple and interpretable models
B) They require minimal data preprocessing
C) They work well with high-dimensional data
D) They combine multiple models to improve predictive performance

3. Which of the following is a common technique for handling missing data in a machine learning pipeline?

A) Deleting rows with missing data
B) Imputing missing values
C) Ignoring missing data
D) Replacing missing values with zeros

4. What is the significance of the "bias-variance trade-off" in machine learning?

A) It refers to the trade-off between the number of features and the model's complexity.
B) It indicates the trade-off between accuracy and precision.
C) It represents the trade-off between underfitting and overfitting.
D) It is not relevant in machine learning.

5. What is the primary purpose of model documentation in the model deployment phase?

A) To provide information on the model's development, architecture, and usage
B) To assess data quality
C) To evaluate the model's accuracy
D) To create synthetic data

Solutions: