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

1. Refer to the following profit matrix and confusion matrix for a campaign soliciting product purchases. The predicted variable is a binary outcome.

Based on the above tables, what is the average profit? You may use a calculator for this question. On the certification exam, an on-screen calculator is provided for you.
Select one:
Response:

A) 6.9
B) 69
C) 690
D) 86.25

2. Look over the output from the Neural Network model. Which of the following statement(s) is (are) true?
Response:

A) All of the above
B) The optimization for the model has not been completed.
C) The misclassification error for the test data is 0.154255.
D) The model has too few input variables.

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

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

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

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

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.
In the training data set, consider only those observations for which the actual value of the target variable equals 1, TARGET=1. What percentage of these observations is being correctly predicted by the decision tree?
Response:

A) 80.3571
B) 14.6216
C) 66.6667
D) 15

Solutions: