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SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions:
1. For the Variable Selection node, which statement describes the R-squared variable selection criterion?
Select one:
Response:
A) It uses a squared correlation and then a stepwise regression to eliminate irrelevant inputs.
B) It looks for a set of colinear inputs that correlate with the target.
C) It uses a chi-squared Decision Tree with no Bonferoni adjustment to select the relevant inputs.
D) It is similar to a decision tree algorithm in being able to detect nonlinear and non-additive relationships between inputs and the target.
2. 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.
Which of the following variables was used in the decision tree model?
Response:
A) TLDel90Cnt24
B) IMP_TLSatCnt
C) InqFinanceCnt24.
D) TLDel3060Cnt24
3. Assume the Target has an event proportion of 2% in the original data. Which of the following property values should be used in the Sample node of SAS Enterprise Miner to create a sample from that data with a balanced 50/50 split for Target?
Select one:
Response:
A) Sample Method: Stratify and Criterion: Proportional
B) Sample Method: Random and Criterion: Equal
C) Sample Method: Stratify and Criterion: Equal
D) Sample Method: Random and Criterion: Proportional
4. Which of the following is not true about results produced by the Regression node?
Response:
A) Model Information provides you with information that includes the number of target categories and the number of model parameters.
B) Fit Statistics can provide information that affects decision predictions, but does not affect estimate predictions.
C) Variable Summary information identifies the roles of variables used by the Regression node.
D) Type 3 Analysis of Effects provides you with information about the number of parameters that each input contributes to the model.
5. 1. Create a project named Insurance, with a diagram named Explore.
2. Create the data source, DEVELOP, in SAS Enterprise Miner. DEVELOP is in the directory c:\workshop\Practice.
3. Set the role of all variables to Input, with the exception of the Target variable, Ins (1= has insurance, 0= does not have insurance).
4. Set the measurement level for the Target variable, Ins, to Binary.
5. Ensure that Branch and Res are the only variables with the measurement level of Nominal.
6. All other variables should be set to Interval or Binary.
7. Make sure that the default sampling method is random and that the seed is 12345.
What is the mean credit card balance (CCBal) of the customers with a variable annuity?
Response:
A) $8,711.65
B) $9,586.55
C) $0.00
D) $11,142.45
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: D | Question # 3 Answer: C | Question # 4 Answer: B | Question # 5 Answer: B |



