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SASInstitute A00-406 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Sources | 30-36% | - Exploring and modifying data - Importing and preparing data - Dimensionality reduction and feature engineering |
| Model Assessment and Deployment | 24-30% | - Deploying models into production - Assessing model performance (metrics, ROC curves, confusion matrices) |
| Building Models | 40-46% | - Model comparison and selection - Supervised model creation (decision trees, ensembles, SVM, neural networks) |
SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions:
1. What is the primary role of a loss function in model training?
A) To measure the difference between predicted and actual values
B) To maximize the model's performance
C) To visualize the data
D) To assess the accuracy of the model
2. When deploying a model, what is "model explainability"?
A) The process of data preprocessing
B) The time it takes to make predictions
C) The capability to interpret and understand the model's decisions and predictions
D) The simplicity of the model
3. 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
4. Which of the following is an example of a NoSQL database that is commonly used to store unstructured data?
A) Microsoft SQL Server
B) MongoDB
C) Oracle Database
D) MySQL
5. What is "model retraining" in the context of model deployment?
A) Periodically updating and improving a deployed model with new data
B) The process of data preprocessing
C) The process of building the initial model
D) The process of feature selection
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: C | Question # 3 Answer: C | Question # 4 Answer: B | Question # 5 Answer: A |
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