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SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions (Q82-Q87):
NEW QUESTION # 82
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. 16-20
- B. 21 or more
- C. 1-10
- D. 11-15
Answer: D
NEW QUESTION # 83
If the bank wanted to select the best model based on the models' overall performances on the validation data as measured by the average squared error, then the best model is which of the following?
Response:
- A. Decision Tree (3-way)
- B. Regression
- C. Neural Network
- D. Decision Tree
Answer: B
NEW QUESTION # 84
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. (L-1)/1
- C. 2L
- D. 2L-1
Answer: A
NEW QUESTION # 85
Which method of input selection for regression analysis evaluates the statistical significance of all included inputs after each input is added?
Select one:
Response:
- A. Stepwise
- B. Forward
- C. Simple
- D. Backward
Answer: A
NEW QUESTION # 86
Consider a binary target variable. Assume Accuracy is the desired assessment measure. Accuracy is not an option in the Decision Tree node. Which assessment measure can you use as a proxy for accuracy?
Select one:
Response:
- A. 1 - Misclassification Rate
- B. Mean Square Error
- C. Average Squared Error
- D. Total Profit
Answer: A
NEW QUESTION # 87
......
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