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SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions (Q35-Q40):

NEW QUESTION # 35
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. TLDel3060Cnt24
B. InqFinanceCnt24.
C. IMP_TLSatCnt
D. TLDel90Cnt24

Answer: A

NEW QUESTION # 36
A useful concept in logistic regression is the doubling amount. How would you calculate doubling amount for an input variable that has a parameter estimate of b1?
Response:

A. 2*b1
B. 2*log(b1)
C. 0.69/b1
D. 2/log(b1)

Answer: C

NEW QUESTION # 37
Refer to the following profit matrix and confusion matrix for a campaign soliciting product purchases. The predicted variable is a binary outcome.

Based on the above tables, what is the average profit? You may use a calculator for this question. On the certification exam, an on-screen calculator is provided for you.
Select one:
Response:

A. 86.25
B. 0
C. 1
D. 6.9

Answer: C

NEW QUESTION # 38
The selected model, based on the misclassification rate for the validation data, has how many input variables?
Response:

A. 0
B. 1
C. 4 or more
D. 2

Answer: B

NEW QUESTION # 39
Suppose your input variables have missing values. Before running a decision tree with these input variables, you should do which of the following?
Response:

A. impute all missing values using the Tree method
B. impute only class variables using the Tree method but do not impute the interval variables
C. impute only interval variables using the Tree method but do not impute the class variables
D. not impute any missing values because trees can handle them.

Answer: D

NEW QUESTION # 40
......

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