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

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SASInstitute A00-406 Exam Syllabus Topics:

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

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

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

2. In the context of model assessment, what does "bias" refer to?

A) The simplicity of the model
B) The process of feature engineering
C) A measure of the model's precision
D) A systematic error that causes a model to consistently overpredict

3. What is the purpose of cross-entropy loss in machine learning, especially in the context of classification?

A) To calculate the mean squared error of a regression model
B) To quantify the variance of a model
C) To evaluate feature importance
D) To measure the dissimilarity between predicted and actual class probabilities

4. What is the main goal of data preprocessing in a machine learning pipeline?

A) To remove irrelevant features
B) To visualize the data
C) To train the model
D) To prepare the data for analysis and modeling

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

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

Solutions: