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SASInstitute A00-255 Exam Syllabus Topics:

SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions:

1. 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) 75 or more
B) 50-74.99
C) 0-24.99
D) 25-49.99

2. Look over the output from the Neural Network model. Which of the following statement(s) is (are) true?
Response:

A) The optimization for the model has not been completed.
B) The model has too few input variables.
C) All of the above
D) The misclassification error for the test data is 0.154255.

3. What is the kurtosis value for the variable TLDel60Cnt24?
Response:

A) between 10 and 13.99
B) less than 10
C) 17 or higher
D) between 14 and 16.99

4. Consider a binary target variable. Assume Accuracy is the desired assessment measure. Accuracy is not an option in the Decision Tree node. Which assessment measure can you use as a proxy for accuracy?
Select one:
Response:

A) Average Squared Error
B) Total Profit
C) 1 - Misclassification Rate
D) Mean Square Error

5. 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) 14.69
C) 5.00
D) 5862.76

Solutions: