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

1. -> Add a Decision Tree node after the Impute node with TARGET as the dependent variable and all other input variables as independent variables (main effects only).
- Allow for 1 substitute rule in case the variable for the primary splitting rule is missing.
- Disable pruning for the decision tree.
-> Add another Neural Network node after the decision tree with TARGET as the dependent variable and all other input variables as independent variables (main effects only).
- Configure the Neural Network model to use Average Error for Model Selection Criterion.
-> Run the process flow.
What is the number of input variables being used by the Neural Network Model?
Enter your numeric answer in the space below:
Response:

A) 13
B) 11
C) 10
D) 16

2. Perform these tasks in SAS Enterprise Miner:
Add a Decision Tree node, as shown below. (Make sure you use only default options in the Decision Tree node.)

Run the Decision Tree node.
Now suppose that the bank expects to make a profit of $200 USD when TARGET=1, but it expects to lose $25 USD when TARGET=0. Incorporate the above scenario, change the assessment measure of the decision tree to average square error, and then run the Decision Tree node. What is the total profit for the test data set?
Response:

A) 300-999
B) 1,000-1,599
C) less than or equal to 299
D) 1,600 or higher

3. Refer to the exhibit:

When the Explore button is selected in the graphic, what information will be displayed?
Select one:
Response:

A) Sample Properties, Sample Statistics for all variables, and sample data for all variables
B) Sample Properties, Sample Statistics, sample data with all variables and values, and a histogram of the data for the selected variable
C) Sample Properties, Sample Statistics, sample data for the selected variable, and a pie chart of the selected variable
D) Sample Properties, Sample Statistics, sample data for the selected variable, and a histogram of the data for the selected variable

4. Assume you have two equally appealing logistic regression models. Then, if you have to select only one out of these two models, you should select the one that has which of the following?
Response:

A) smaller value of gamma
B) higher value of AIC (Akaike,s information criterion)
C) smaller value of SBC (Schwarz,s Bayesian criterion)
D) all of the above

5. Which model was picked as the best model by SAS Enterprise Miner?
Response:

A) None of the above
B) Decision Tree (3-way)
C) Decision Tree
D) Regression

Solutions: