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SASInstitute A00-406 Exam Syllabus Topics:

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

Question 1

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

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

Question 2

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

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

Question 3

What is the primary purpose of a supervised machine learning pipeline in SAS Viya?

A. Data visualization
B. Model training and evaluation
C. Data storage and retrieval
D. Data preprocessing and cleaning

Question 4

In model evaluation, what is the purpose of a ROC curve (Receiver Operating Characteristic)?

A. To measure feature importance
B. To compare models' performance in terms of sensitivity and specificity
C. To evaluate the mean squared error of a model
D. To visualize data distribution

Question 5

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

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

Solutions: