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SASInstitute A00-255 (SAS Predictive Modeling Using SAS Enterprise Miner 14) Certification Exam is a rigorous exam that requires candidates to fully understand the principles of predictive analytics and how to apply them using SAS Enterprise Miner 14. Candidates must be able to demonstrate their ability to analyze complex data, build predictive models, and evaluate the quality of their results. A00-255 exam is intended for individuals who want to demonstrate their ability to work with advanced SAS software to solve complex business problems or engage in commercial research.

The A00-255 Certification Exam is a performance-based test that evaluates the candidates' ability to apply their knowledge in a real-world scenario. To pass the exam, the candidates need to demonstrate their proficiency in using SAS Enterprise Miner to solve complex business problems. A00-255 exam consists of 50 multiple-choice questions, and the candidates are given 110 minutes to complete the test.

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SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions (Q18-Q23):

NEW QUESTION # 18
What is the kurtosis value for the variable TLDel60Cnt24?
Response:

A. 17 or higher
B. between 14 and 16.99
C. less than 10
D. between 10 and 13.99

Answer: B

NEW QUESTION # 19
For the variable TLCnt24, apply a Max Normal transformation. What transformation was selected by SAS Enterprise Miner?
Response:

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

Answer: B

NEW QUESTION # 20
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. 0.42667
B. 0.60485
C. 0.32959
D. 0.42541

Answer: B

NEW QUESTION # 21
In segment 2, what percentage of GiftAvgCard36 values are between 6.6638 and 11.998?
Select one:
Response:

A. 48.59%
B. 14.00%
C. 47.82%
D. 13.39%

Answer: A

NEW QUESTION # 22
The importance of an input variable in predicting a target in an MLP-based neural network can be figured out by which of the following?
Response:

A. none of the above
B. the highest absolute value of the parameter estimate between the input and any of the hidden neurons
C. the average of the absolute values of parameter estimates between the input and all of the hidden neurons
D. the highest absolute value of the parameter estimate between the input and any of the hidden neurons multiplied by the absolute value of the parameter estimate of the hidden neuron

Answer: A

NEW QUESTION # 23
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