SASInstitute SAS® Viya® Supervised Machine Learning Pipelines : A00-406

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SASInstitute A00-406 Exam Syllabus Topics:

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

1. Which technique is used for feature selection in a machine learning pipeline when dealing with a large number of features?

A) Naive Bayes
B) Regularization
C) One-Hot Encoding
D) Principal Component Analysis (PCA)

2. In the context of data sources, what is meant by data versioning?

A) Compressing data to reduce storage space
B) Encrypting data to protect against unauthorized access
C) Keeping track of different versions or changes to data over time
D) Storing multiple copies of the same data to increase redundancy

3. Which of the following metrics is commonly used to evaluate the performance of a binary classification model in a machine learning pipeline?

A) Accuracy
B) Mean Absolute Error (MAE)
C) R-squared
D) Root Mean Squared Error (RMSE)

4. What is the primary difference between supervised and unsupervised learning in model building?

A) The presence or absence of a target variable
B) The type of data used
C) The use of feature engineering
D) The amount of labeled data required

5. What is "model retraining" in the context of model deployment?

A) The process of feature selection
B) The process of building the initial model
C) The process of data preprocessing
D) Periodically updating and improving a deployed model with new data

Solutions: