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SASInstitute A00-255 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Business Understanding and Analytical Framework | - Translate business problems into data mining tasks - Define business objectives and analytics goals |
| Model Evaluation and Validation | - Model performance metrics - Validation and cross-validation techniques - Model comparison and selection |
| Exploratory Data Analysis | - Descriptive statistics and data profiling - Visualization techniques for pattern discovery |
| Model Implementation and Deployment | - Monitoring model performance in production - Model scoring and deployment in SAS Enterprise Miner |
| Data Understanding and Preparation | - Data cleaning and preprocessing - Handling missing values and outliers - Feature selection and transformation - Data collection and data source identification |
| Model Development | - Regression modeling techniques - Decision trees and ensemble methods - Neural networks and advanced modeling in SAS Enterprise Miner |
SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions:
Open the diagram labeled Practice A within the project labeled Practice A. Perform the following in SAS Enterprise Miner:
1. Set the Clustering method to Average.
2. Run the Cluster node.
What is the Cubic Clustering Criterion statistic for this clustering?
Response:
- A. 67409.93
- B. 5.00
- C. 5862.76
- D. 14.69
Correct Answer: D 🗳️
Open the diagram labeled Practice A within the project labeled Practice A. Perform the following in SAS Enterprise Miner:
1. Set the Clustering method to Average.
2. Run the Cluster node.
What is the Cubic Clustering Criterion statistic for this clustering?
Response:
- A. 67409.93
- B. 5.00
- C. 5862.76
- D. 14.69
Correct Answer: D 🗳️
Which method of input selection for regression analysis evaluates the statistical significance of all included inputs after each input is added?
Select one:
Response:
- A. Forward
- B. Backward
- C. Simple
- D. Stepwise
Correct Answer: D 🗳️
Perform these tasks in SAS Enterprise Miner:
- Use the Regression node to build another regression model with TARGET as the dependent variable and all other input variables as independent variables (main effects only).
- Configure the regression model to use Stepwise for Selection Model and Validation Error for Selection Criteri a. Do not change any other property for the regression model.
For the validation data, in what range does cumulative percent captured response at the 60th percentile lie?
Response:
- A. 50-74.99
- B. 25-49.99
- C. 0-24.99
- D. 75 or more
Correct Answer: D 🗳️
If the bank wanted to select the best model based on which model achieves the highest lift for the third decile in the validation data, then which of the following is the best model?
Response:
- A. Regression
- B. Decision Tree
- C. Neural Network
- D. Decision Tree (3-way)
Correct Answer: B 🗳️
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