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SASInstitute A00-255 exam is suitable for individuals who are proficient in SAS programming and have experience in data preparation, data mining, and data analysis. A00-255 exam objectives include understanding data exploration, data preparation, variable selection, modeling, and model assessment. A00-255 Exam also covers advanced modeling techniques, such as decision trees, neural networks, and ensemble models.

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SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions (Q47-Q52):

NEW QUESTION # 47
The number of neurons in this Neural Network model is which of the following:
Response:

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

Answer: C

NEW QUESTION # 48
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. 11-15
D. less than or equal to 10

Answer: A

NEW QUESTION # 49
Which method of input selection for regression analysis evaluates the statistical significance of the total model to see if it improves on the baseline as the variables are added and once no further improvement is made then variable selection ends?
Select one:
Response:

A. Backward
B. Forward
C. Stepwise
D. Simple

Answer: B

NEW QUESTION # 50
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/log(b1)
B. 2*log(b1)
C. 0.69/b1
D. 2*b1

Answer: C

NEW QUESTION # 51
For the variable TLCnt24, apply a Max Normal transformation. What transformation was selected by SAS Enterprise Miner?
Response:

A. Log
B. Square
C. Exponential
D. Square Root

Answer: D

NEW QUESTION # 52
......

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