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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Sources | 20-25% | - Prepare Source Data
|
| Topic 2: Building Predictive Models | 35-40% | - Model Development
|
| Topic 3: Predictive Model Assessment and Implementation | 25-30% | - Model Deployment
|
| Topic 4: Pattern Analysis | 10-15% | - Segmentation and Association Analysis
|
1. 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) 0.60485
C) 0.42667
D) 0.42541
2. 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) $9,586.55
B) $0.00
C) $11,142.45
D) $8,711.65
3. 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) 16-20
B) 21 or more
C) less than or equal to 10
D) 11-15
4. What is the kurtosis value for the variable TLDel60Cnt24?
Response:
A) between 10 and 13.99
B) less than 10
C) 17 or higher
D) between 14 and 16.99
5. Impute the missing values for the variable TLSum using the Tree method. What is the mean of the new variable (with the imputed values)?
Response:
A) 30,000-39,999.99
B) 40,000 or higher
C) 20,000-29,999.99
D) less than 19,999.99
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: A | Question # 3 Answer: A | Question # 4 Answer: D | Question # 5 Answer: D |
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