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

1. Which of the following is not a good reason to"regularize" input distributions using a simple transformation?
Response:

A) One benefit is improved model performance.
B) When you perform regression, inputs with highly skewed or highly kurtotic distributions can be selected over inputs that would yield better overall predictions.
C) Another benefit is ease in model interpretation.
D) Regression models are sensitive to extreme or outlying values in the input space.

2. Assume a variable is coded as follows: 1=unmarried, 2=married, 3=divorced, and 4=widowed. Then which of the following measurement levels should be selected in SAS Enterprise Miner for this variable?
Response:

A) Ordinal
B) Unary
C) Nominal
D) Interval

3. 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 dat a. 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 distribution of the predicted probabilities of TARGET=0 in the scoring data is approximately which of the following?
Response:

A) left skewed
B) right skewed
C) normal
D) bimodal

4. What percentage of observations in the test data has TARGET=1?
Response:

A) 83.3333
B) 16.8874
C) 16.6627
D) 16.5924

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.
For the validation data, in what range does cumulative percent captured response at the 60th percentile lie?
Response:

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

Solutions: