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SASInstitute A00-406 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Sources | 30-36% | - Reduce dimensionality - Create a project in Model Studio - Perform variable selection - Modify and prepare data - Explore and understand data |
| Building Models | 40-46% | - Build neural networks and SVM models - Build regression models - Understand supervised machine learning concepts - Use model interpretability tools - Build decision trees and ensemble models - Integrate custom code |
| Model Assessment and Deployment | 24-30% | - Select champion models - Evaluate and compare model performance - Apply model assessment principles - Deploy models into production |
SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions:
Refer to the exhibit below:
Based on the output from the Data Exploration node shown in the exhibit, which variable has the most thin tails (most platykurtic distribution)?
- A. Logi_rfm4
- B. Logi_rfm8
- C. Logi_rfm12
- D. Logi_rfm6
Correct Answer: C 🗳️
Which of the following is NOT a common data format for exchanging data between systems?
- A. HTML (Hypertext Markup Language)
- B. SQL (Structured Query Language)
- C. CSV (Comma-Separated Values)
- D. JSON (JavaScript Object Notation)
Correct Answer: B 🗳️
In model assessment, what is the purpose of feature importance analysis?
- A. To create synthetic features
- B. To visualize data distribution
- C. To evaluate the significance of input features in making predictions
- D. To assess data quality
Correct Answer: C 🗳️
Which evaluation metric is commonly used for assessing the performance of a binary classification model?
- A. Accuracy
- B. R-squared
- C. Root Mean Squared Error (RMSE)
- D. Mean Absolute Error (MAE)
Correct Answer: A 🗳️
What is the primary role of a loss function in model training?
- A. To maximize the model's performance
- B. To visualize the data
- C. To measure the difference between predicted and actual values
- D. To assess the accuracy of the model
Correct Answer: C 🗳️
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