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

1. Transformation of input variables to make their distributions more symmetric will likely have what impact in a logistic regression?
Select one:
Response:

A) neither increase nor decrease the performance of logistic regression
B) decrease the performance of logistic regression
C) increase the performance of logistic regression
D) create convergence problems in maximum likelihood estimation

2. 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) none of the above
C) the highest absolute value of the parameter estimate between the input and any of the hidden neurons
D) 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

3. For the variable InqCnt06, replace all values over 10.1 with the value 10. How many values are replaced?
Response:

A) 100-149
B) 0-99
C) 150-199
D) 200 or higher

4. 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) 25-49.99
B) 50-74.99
C) 0-24.99
D) 75 or more

5. 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.
What percentage of all observations is being correctly predicted in the test data set by the decision tree?
Response:

A) 83.1126%
B) 16.8874%
C) 84.5212%
D) 85.2222%

Solutions: