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SASInstitute A00-255 Exam Syllabus Topics:

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

1. -> Add a Decision Tree node after the Impute node with TARGET as the dependent variable and all other input variables as independent variables (main effects only).
- Allow for 1 substitute rule in case the variable for the primary splitting rule is missing.
- Disable pruning for the decision tree.
-> Add another Neural Network node after the decision tree with TARGET as the dependent variable and all other input variables as independent variables (main effects only).
- Configure the Neural Network model to use Average Error for Model Selection Criterion.
-> Run the process flow.
What is the number of input variables being used by the Neural Network Model?
Enter your numeric answer in the space below:
Response:

A) 11
B) 10
C) 16
D) 13

2. 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

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

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

4. Which model was picked as the best model by SAS Enterprise Miner?
Response:

A) Decision Tree (3-way)
B) Regression
C) Decision Tree
D) None of the above

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) 14.69
B) 67409.93
C) 5.00
D) 5862.76

Solutions: