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Achieving the SASInstitute A00-255 certification demonstrates that a candidate has the skills and knowledge required to build and deploy predictive models using SAS Enterprise Miner. SAS Predictive Modeling Using SAS Enterprise Miner 14 certification is recognized globally and is highly valued by organizations that use SAS software for data analysis and predictive modeling. Earning this certification can enhance a candidate's career prospects by demonstrating their proficiency in using SAS Enterprise Miner and their commitment to professional development.

The A00-255 exam covers a wide range of topics related to predictive modeling using SAS Enterprise Miner. This includes data exploration, data preparation, variable selection, model selection, model assessment, and deployment. Candidates are expected to demonstrate their ability to apply these concepts to real-world data mining problems using SAS Enterprise Miner. A00-255 Exam is conducted in a proctored environment and consists of multiple-choice questions and interactive questions.

Passing the SASInstitute A00-255 exam is a great way to showcase your expertise in the field of predictive modeling using SAS Enterprise Miner. SAS Predictive Modeling Using SAS Enterprise Miner 14 certification can help you stand out from other professionals in your industry, and it can also give you a competitive edge when it comes to finding new job opportunities. Additionally, becoming SAS certified can increase your earning potential and improve your credibility as a data analyst or data scientist. Whether you are looking to enhance your career prospects or simply want to deepen your knowledge of predictive modeling with SAS Enterprise Miner, the A00-255 exam is an excellent choice.

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SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions (Q21-Q26):

NEW QUESTION # 21
For the variable TLCnt24, apply a Max Normal transformation. What transformation was selected by SAS Enterprise Miner?
Response:

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

Answer: D

NEW QUESTION # 22
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. 67409.93
B. 5862.76
C. 5.00
D. 14.69

Answer: D

NEW QUESTION # 23
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. TLDel3060Cnt24
B. TLDel90Cnt24
C. InqFinanceCnt24.
D. IMP_TLSatCnt

Answer: A

NEW QUESTION # 24
What is the kurtosis value for the variable TLDel60Cnt24?
Response:

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

Answer: A

NEW QUESTION # 25
How many unique indicator variables were created during imputation?
Response:

A. 11-20
B. none
C. 1-10
D. 21 or higher

Answer: A

NEW QUESTION # 26
......

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