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

1. Suppose your input variables have missing values. Before running a decision tree with these input variables, you should do which of the following?
Response:

A) impute all missing values using the Tree method
B) impute only interval variables using the Tree method but do not impute the class variables
C) impute only class variables using the Tree method but do not impute the interval variables
D) not impute any missing values because trees can handle them.

2. In segment 2, what percentage of GiftAvgCard36 values are between 6.6638 and 11.998?
Select one:
Response:

A) 47.82%
B) 48.59%
C) 14.00%
D) 13.39%

3. Assume that a company has an excellent customer segmentation in place and the segment scheme is a variable in the input data set. What is the best partition method that one should use?
Select one:
Response:

A) Stratify
B) Random
C) Cluster
D) Systemic

4. 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

5. 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) 86.25
B) 690
C) 6.9
D) 69

Solutions: