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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.
How many leaves are there in the decision tree?
Response:

A) 1-10
B) 21 or more
C) 11-15
D) 16-20

2. How many hidden layers are generally needed in an MLP-based neural network to capture a discontinuous relationship between inputs and target?
Response:

A) one hidden layer
B) three or more hidden layers
C) two hidden layers
D) no hidden layer, direct connection between inputs and output is preferred

3. What is the purpose of the Kass (Bonferroni) adjustment in the decision tree split-search algorithm?
Select one:
Response:

A) To ensure that the choice of split is not influenced by input measurement scale.
B) To ensure a non-negative logworth value.
C) To reduce the number of surrogate splitting rules.
D) To give categorical inputs a greater chance to be used the split.

4. Perform these tasks in SAS Enterprise Miner:
- Use the Regression node to build another regression model with TARGET as the dependent variable and all other input variables as independent variables (main effects only).
- Configure the regression model to use Stepwise for Selection Model and Validation Error for Selection Criteri a. Do not change any other property for the regression model.
Consider the variable TLCnt03 in the selected model. Based on the model results, changing this variable by 1 unit will result in which of the following?
Response:

A) reduction of odds for TARGET=1 by 0.3457
B) reduction of odds for TARGET=1 by 0.708
C) change of odds for TARGET=1 by a factor 0.3457
D) change of odds for TARGET=1 by a factor 0.708

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 Importance statistic for MTGBal (Mortgage Balance)?
Response:

A) 0.32959
B) 0.42541
C) 0.42667
D) 0.60485

Solutions: