SASInstitute A00-255 : SAS Predictive Modeling Using SAS Enterprise Miner 14

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

1. 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.
Consider the variable TLCnt03 in the selected model. Based on the model results, changing this variable by 1 unit will result in which of the following?
Response:

A) change of odds for TARGET=1 by a factor 0.708
B) reduction of odds for TARGET=1 by 0.708
C) change of odds for TARGET=1 by a factor 0.3457
D) reduction of odds for TARGET=1 by 0.3457

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

3. For the Variable Selection node, which statement describes the R-squared variable selection criterion?
Select one:
Response:

A) It looks for a set of colinear inputs that correlate with the target.
B) It uses a chi-squared Decision Tree with no Bonferoni adjustment to select the relevant inputs.
C) It is similar to a decision tree algorithm in being able to detect nonlinear and non-additive relationships between inputs and the target.
D) It uses a squared correlation and then a stepwise regression to eliminate irrelevant inputs.

4. Choose the correct statement that illustrates Decision Tree Split Search for continuous (interval) inputs:
Select one:
Response:

A) Each unique value has the potential of being the optimal split point, except for the extreme observation.
B) The variable goes through a non-linear transformation, and the transformed variable is used for testing.
C) Each unique value has the potential of being the optimal split point.
D) The variable goes through a binning process, the bins are weighted based on the proportion of events in each bin, and then finally tested as an optimal split point.

5. In SAS Enterprise Miner's Decision Tree node, which of the following types of target variable can be used?
Response:

A) all of the above
B) nominal with any number of categories
C) interval
D) binary

Solutions: