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SASInstitute A00-406 Exam Syllabus Topics:

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

1. In a supervised machine learning pipeline, what is the purpose of the test data set?

A) To validate the model's performance
B) To train the machine learning model
C) To evaluate the model's predictions
D) To preprocess the data

2. 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

3. What is the purpose of an ROC curve (Receiver Operating Characteristic) in model assessment?

A) To compare a model's true positive rate with the false positive rate
B) To visualize data distribution
C) To measure feature importance
D) To evaluate regression models

4. In a machine learning pipeline, what is the purpose of cross-validation?

A) To train multiple models on different subsets of the data to assess generalization
B) To visualize the data distribution
C) To split the dataset into training and testing sets
D) To evaluate the model's performance on new data

5. What is the purpose of data profiling in data source management?

A) To assess the quality and characteristics of data
B) To optimize data storage
C) To execute data queries
D) To create data visualizations

Solutions: