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SASInstitute A00-406 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Model Assessment and Deployment | 24-30% | - Deploying models into production - Assessing model performance (metrics, ROC curves, confusion matrices) |
| Data Sources | 30-36% | - Exploring and modifying data - Importing and preparing data - Dimensionality reduction and feature engineering |
| Building Models | 40-46% | - Supervised model creation (decision trees, ensembles, SVM, neural networks) - Model comparison and selection |
SASInstitute SAS® Viya® Supervised Machine Learning Pipelines Sample Questions:
Which type of model is typically used for time-series forecasting?
- A. Decision Trees
- B. AutoRegressive Integrated Moving Average (ARIMA)
- C. Logistic Regression
- D. K-Means Clustering
What is the purpose of data profiling in data source management?
- A. To optimize data storage
- B. To assess the quality and characteristics of data
- C. To create data visualizations
- D. To execute data queries
What is the primary role of a data warehouse in an organization?
- A. Real-time data analysis
- B. Long-term data storage and analysis
- C. Data transformation and cleaning
- D. Data exploration and visualization
Refer to the treemap shown in the exhibit below:
Which statement is true about the tree map for a decision tree with a binary target?
- A. The wider bars represent nodes with a higher probability of event.
- B. The top bar represents the node with the highest probability of event.
- C. The top bar represents the node with the highest count.
- D. The darker bars represent nodes with a lower probability of event.
In model assessment, what does "cross-validation" aim to address?
- A. Training a model
- B. Overfitting and generalization
- C. Model deployment
- D. Data preprocessing
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