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SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions (Q45-Q50):

NEW QUESTION # 45
Perform these tasks in SAS Enterprise Miner:
*Continue to use the same diagram. Define and create the data set CREDIT_SCORE for scoring. The variables (their roles and measurement levels) in the CREDIT_SCORE data should be set as identical to those in the CREDIT dat a. The only exception is that the scoring data does not have a TARGET variable.
* Find the best model out of Decision Tree, Decision Tree (3-way), Regression, and Neural Network as defined by each of the four model's overall performance in the validation data measured by average squared error. Now, use this best model to score the CREDIT_SCORE data.
CREDIT SCORE:

The percentage of TARGET=1 as predicted by the best model on the scoring data is in which of the following ranges?
Response:

A. 7% or higher
B. under 4.99%
C. 6%-6.99%
D. 5%-5.99%

Answer: B

NEW QUESTION # 46
Assume you have two equally appealing logistic regression models. Then, if you have to select only one out of these two models, you should select the one that has which of the following?
Response:

A. smaller value of SBC (Schwarz,s Bayesian criterion)
B. all of the above
C. smaller value of gamma
D. higher value of AIC (Akaike,s information criterion)

Answer: A

NEW QUESTION # 47
The Chi Square statistic for measuring association between the variables BanruptcyInd and TARGET is which of the following?
Response:

A. less than 1.00
B. between 1.00 and 1.99
C. 3.00 or higher
D. between 2.00 and 2.99

Answer: B

NEW QUESTION # 48
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. 6.9
B. 86.25
C. 0
D. 1

Answer: D

NEW QUESTION # 49
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. InqFinanceCnt24.
B. IMP_TLSatCnt
C. TLDel3060Cnt24
D. TLDel90Cnt24

Answer: C

NEW QUESTION # 50
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