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

1. Which of the following sequential selection methods do you use so that SAS Enterprise Miner will look at all variables already included in the model and delete any variable that is not significant at the specified level?
Response:

A) Forward
B) Stepwise
C) Backward
D) None

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

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

3. 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 is the probability that TARGET=0 for ID=000355 in the training data?
Response:

A) 0.9341825902
B) 0.9220647773
C) 0.077935227
D) 0.0658174098

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.
B) 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.
C) Each unique value has the potential of being the optimal split point, except for the extreme observation.
D) The variable goes through a non-linear transformation, and the transformed variable is used for testing.

5. Assume the Target has an event proportion of 2% in the original data. Which of the following property values should be used in the Sample node of SAS Enterprise Miner to create a sample from that data with a balanced 50/50 split for Target?
Select one:
Response:

A) Sample Method: Random and Criterion: Proportional
B) Sample Method: Stratify and Criterion: Proportional
C) Sample Method: Random and Criterion: Equal
D) Sample Method: Stratify and Criterion: Equal

Solutions: