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SASInstitute A00-255 Exam is a certification designed for professionals who are interested in working with the SAS Enterprise Miner software program. A00-255 exam is targeted towards individuals who want to master the art of predictive modeling and analysis in their workplace. The SASInstitute A00-255 Exam is designed to test the candidate's knowledge of the SAS Enterprise Miner 14 software application.

SASInstitute A00-255 certification exam is an excellent opportunity for individuals seeking to enhance their skills in predictive modeling using SAS Enterprise Miner 14. It validates one's knowledge and expertise in data mining and predictive modeling and provides a competitive edge in the job market. With the right preparation and practice, passing A00-255 Exam can significantly boost one's career prospects in the field of data science.

To appear for the SASInstitute A00-255 Certification Exam, candidates must have a strong understanding of SAS programming basics, statistical modeling concepts, and data mining techniques. A00-255 exam focuses on various topics, such as data exploration, data transformation, variable selection, model comparison, and model deployment. Candidates must also have experience working with SAS Enterprise Miner software to analyze and model data effectively. Passing the SASInstitute A00-255 Certification Exam demonstrates that a candidate has the necessary skills and knowledge to use SAS Enterprise Miner effectively for predictive modeling and data analysis.

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SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions (Q80-Q85):

NEW QUESTION # 80
For the variable InqCnt06, replace all values over 10.1 with the value 10. How many values are replaced?
Response:

A. 200 or higher
B. 100-149
C. 0-99
D. 150-199

Answer: B

NEW QUESTION # 81
Which model was picked as the best model by SAS Enterprise Miner?
Response:

A. Decision Tree
B. None of the above
C. Regression
D. Decision Tree (3-way)

Answer: A

NEW QUESTION # 82
In SAS Enterprise Miner's Decision Tree node, which of the following types of target variable can be used?
Response:

A. all of the above
B. nominal with any number of categories
C. binary
D. interval

Answer: A

NEW QUESTION # 83
The selected model, based on the misclassification rate for the validation data, has how many input variables?
Response:

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

Answer: D

NEW QUESTION # 84
If the bank wanted to select the best model based on which model achieves the highest lift for the third decile in the validation data, then which of the following is the best model?
Response:

A. Neural Network
B. Decision Tree
C. Regression
D. Decision Tree (3-way)

Answer: B

NEW QUESTION # 85
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