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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 after the Impute node with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the decision tree to use 1 for Number of Surrogate Rules and Largest for Method in Subtree. Do not change any other property of the Decision Tree node.
- 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. Do not change any other property for the Neural Network node. Run the process flow.
The number of input variables being used by the Neural Network model is which of the following?
Response:

A) 21 or more
B) less than or equal to 10
C) 11-15
D) 16-20

2. Sometimes in predictive modeling we build models using a sample that has a primary outcome proportion different from true population proportion. This is usually done when the ratio of primary to secondary outcomes in a binary target variable in the population is close to which of the following?
Response:

A) 0.05
B) 0.8
C) 1
D) 1.2

3. A multilayer perceptron neural network is using three interval inputs to model one interval target (outcome). The neural network has ten hidden units and one hidden layer. How many weights, including biases are being estimated?
You may use a calculator for this question. On the certification exam, an on-screen calculator is provided for you.
Select one:
Response:

A) 50
B) 40
C) 41
D) 51

4. For an ordinal variable with L levels, the number of possible splits in a decision tree is which of the following?
Response:

A) 2L-1-1
B) 2L-1
C) 2L
D) (L-1)/1

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

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

Solutions: