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

1. 1. Create a project named Insurance, with a diagram named Explore.
2. Create the data source, DEVELOP, in SAS Enterprise Miner. DEVELOP is in the directory c:\workshop\Practice.
3. Set the role of all variables to Input, with the exception of the Target variable, Ins (1= has insurance, 0= does not have insurance).
4. Set the measurement level for the Target variable, Ins, to Binary.
5. Ensure that Branch and Res are the only variables with the measurement level of Nominal.
6. All other variables should be set to Interval or Binary.
7. Make sure that the default sampling method is random and that the seed is 12345.
The variable Branch has how many levels?
Response:

A) 19
B) 12
C) 8
D) 47

2. 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.
Which of the following variable(s) is (are) statistically significant at the 5% level in the selected model?
Response:

A) IMP_TLOpen24Pct
B) TLTimeFirst
C) all of the above
D) TLDel3060Cnt24

3. Sometimes in predictive modeling we build models using a sample that has a primary outcome proportion different from true population proportion. This is usually done when the ratio of primary to secondary outcomes in a binary target variable in the population is close to which of the following?
Response:

A) 0.05
B) 1.2
C) 0.8
D) 1

4. The importance of an input variable in predicting a target in an MLP-based neural network can be figured out by which of the following?
Response:

A) the average of the absolute values of parameter estimates between the input and all of the hidden neurons
B) the highest absolute value of the parameter estimate between the input and any of the hidden neurons multiplied by the absolute value of the parameter estimate of the hidden neuron
C) the highest absolute value of the parameter estimate between the input and any of the hidden neurons
D) none of the above

5. What is the average squared error in the training data?
Response:

A) 0.131583
B) 0.133665
C) 0.131709
D) 0.131208

Solutions: