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

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

2. Perform these tasks in SAS Enterprise Miner:
* Continue to use the same diagram. Define and create the data set CREDIT_SCORE for scoring. The variables (their roles and measurement levels) in the CREDIT_SCORE data should be set as identical to those in the CREDIT data. The only exception is that the scoring data does not have a TARGET variable.
* Find the best model out of Decision Tree, Decision Tree (3-way), Regression, and Neural Network as defined by each of the four model's overall performance in the validation data measured by average squared error. Now, use this best model to score the CREDIT_SCORE data.
CREDIT SCORE:

The median of the predicted probabilities of TARGET=1 in the scoring data is in which of the following ranges?
Response:

A) 0.85 or more
B) 0.50-0.849999
C) 0.15-0.499999
D) less than 0.149999

3. Assume that a company has an excellent customer segmentation in place and the segment scheme is a variable in the input data set. What is the best partition method that one should use?
Select one:
Response:

A) Stratify
B) Cluster
C) Random
D) Systemic

4. 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.
Suppose that the data has been oversampled and the probability that TARGET=1 is 0.10 in the population. Incorporate the above scenario and run the Decision Tree node again.
What is the misclassification rate in the validation data set?
Response:

A) 0.157016
B) 0.162252
C) 0.10
D) 0.154788

5. 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) TLDel3060Cnt24
B) IMP_TLOpen24Pct
C) TLTimeFirst
D) all of the above

Solutions: