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SASInstitute A00-406 Exam Syllabus Topics:

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

1. When deploying a machine learning model, what is "model drift"?

A) The process of feature extraction
B) A sudden increase in the model's accuracy
C) A change in the distribution of the input data or target variable over time
D) A measure of feature importance

2. What is a common example of an external data source for an organization?

A) Intranet portals
B) Internal emails
C) Employee databases
D) Customer surveys

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

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

4. Which feature extraction method can take both interval variables and class variables as inputs?

A) Robust PCA
B) Principal component analysis
C) Singular value decomposition
D) Autoencoder

5. Which type of data source typically stores structured data in a tabular format?

A) APIs
B) NoSQL databases
C) Text documents
D) Relational databases

Solutions: