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Latest A00-255 Exam Cost, Actual A00-255 Test Answers

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The SAS Predictive Modeling Using SAS Enterprise Miner 14 is a certification exam offered by SAS Institute. A00-255 Exam is designed to test the candidate's knowledge and skills in SAS predictive modeling using SAS Enterprise Miner. SAS Enterprise Miner is a powerful data mining tool used for data analysis and modeling. It helps in building predictive models and identifying patterns in large datasets. SAS Predictive Modeling Using SAS Enterprise Miner 14 certification exam is a great way for professionals to demonstrate their expertise in this field.

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SASInstitute A00-255 exam is designed to test the skills and knowledge of individuals in the field of predictive modeling using SAS Enterprise Miner 14. SAS Enterprise Miner is a software suite that enables users to create predictive models and perform data mining tasks using a graphical interface. A00-255 Exam is intended for professionals who work with large datasets and want to gain expertise in predictive modeling techniques.

SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions (Q17-Q22):

NEW QUESTION # 17
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. Regression
B. Neural Network
C. Decision Tree
D. Decision Tree (3-way)

Answer: A

NEW QUESTION # 18
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. under 4.99%
B. 6%-6.99%
C. 5%-5.99%
D. 7% or higher

Answer: A

NEW QUESTION # 19
What is the kurtosis value for the variable TLDel60Cnt24?
Response:

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

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 Cubic Clustering Criterion statistic for this clustering?
Response:

A. 14.69
B. 67409.93
C. 5.00
D. 5862.76

Answer: A

NEW QUESTION # 21
Look over the output from the Neural Network model. Which of the following statement(s) is (are) true?
Response:

A. The optimization for the model has not been completed.
B. The misclassification error for the test data is 0.154255.
C. The model has too few input variables.
D. All of the above

Answer: A

NEW QUESTION # 22
......

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