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

1. 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.
Suppose that the data has been oversampled and the probability that TARGET=1 is 0.10 in the population. Incorporate the above scenario and run the Decision Tree node again.
What is the misclassification rate in the validation data set?
Response:

A) 0.162252
B) 0.10
C) 0.157016
D) 0.154788

2. What is the variable worth of the PromCntCardAll variable in Segment 1?
Select one:
Response:

A) 0.10844
B) 0.24169
C) 0.27649
D) 0.24914

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

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

4. The number of hidden layers in this Neural Network model is which of the following?
Response:

A) 2
B) 3
C) 1
D) 4 or more

5. Open the diagram labeled Practice A within the project labeled Practice A. Perform the following in SAS Enterprise Miner:

1. Set the Clustering method to Average.
2. Run the Cluster node.
What is the Cubic Clustering Criterion statistic for this clustering?
Response:

A) 5.00
B) 67409.93
C) 14.69
D) 5862.76

Solutions: