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SASInstitute A00-406 Exam Syllabus Topics:

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

1. In machine learning, what does "overfitting" refer to?

A) A model that performs well on new, unseen data
B) A model that is undertrained and has high bias
C) A model that has too much complexity and fits the training data too closely
D) A model that is unable to make predictions

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

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

3. In model assessment, what is the purpose of feature importance analysis?

A) To assess data quality
B) To visualize data distribution
C) To evaluate the significance of input features in making predictions
D) To create synthetic features

4. What does "data lineage" refer to in the context of data source management?

A) The security protocols for data access
B) The physical location of data storage
C) The history of data transformation processes
D) The structure of a relational database

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

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

Solutions: