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SASInstitute A00-406 Exam Syllabus Topics:

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

1. Which statements are true for the F1 score?
(Choose 2.)

A) F1 score is applicable to a model with an interval target.
B) F1 score is calculated based on a cut off value.
C) F1 score is applicable to a model with a binary target.
D) F1 score is calculated based on a depth value.

2. When assessing a classification model, what is the confusion matrix used to measure?

A) Precision and recall
B) Data distribution
C) Model complexity
D) Model accuracy

3. What is the significance of the "bias-variance trade-off" in machine learning?

A) It indicates the trade-off between accuracy and precision.
B) It represents the trade-off between underfitting and overfitting.
C) It is not relevant in machine learning.
D) It refers to the trade-off between the number of features and the model's complexity.

4. A project has been created and a pipeline has been run in Model Studio.
Which project setting can you edit?

A) Advisor Options for missing values
B) Event-based Sampling proportions
C) Rules for model comparison statistic
D) Partition Data percentages

5. When building a recommendation system, what does "collaborative filtering" rely on?

A) The characteristics of the items being recommended
B) The popularity of items
C) The past behavior or preferences of users
D) Item-based clustering

Solutions: