100% Pass Quiz 2025 SASInstitute A00-255: SAS Predictive Modeling Using SAS Enterprise Miner 14 Unparalleled Examinations Actual Questions

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SASInstitute A00-255 certification exam covers a wide range of topics, including data preparation, variable selection, model selection, model assessment, and model deployment. A00-255 exam is designed to test the candidate's ability to apply statistical techniques and machine learning algorithms to large datasets to develop accurate predictive models. Candidates will be required to demonstrate their proficiency in using SAS Enterprise Miner to create, evaluate, and deploy predictive models.

SASInstitute A00-255 certification exam is a must-have for anyone who wants to improve their skills in predictive modeling using SAS Enterprise Miner. Passing the exam demonstrates your knowledge and skills in handling complex data scenarios and predictive modeling techniques. SAS Predictive Modeling Using SAS Enterprise Miner 14 certification is globally recognized and will help you stand out in the job market, increasing your chances of getting hired or promoted to advanced data analytics roles.

SASInstitute A00-255 Exam is intended for professionals who have experience with SAS programming, statistical analysis, and data mining. A00-255 exam is ideal for data analysts, statisticians, and data scientists who want to advance their skills in predictive modeling using SAS Enterprise Miner 14. A00-255 exam is also suitable for IT professionals who want to develop expertise in data analytics and predictive modeling.

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SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions (Q10-Q15):

NEW QUESTION # 10
You are building a model to identify fraud. Your model will produce predictions that can be interpreted as the probability of fraud. You will pass on the top 100 scoring cases to management for investigation. Assume that you have sufficient data to hold out a validation and test data set for model evaluation.
Which selection would represent a reasonable ordering of fit statistics (best to worst) for this situation?
Select one:
Response:

A. R-square, AIC, K-S statistic
B. ASE, Lift for the top 10%, ROC index
C. ROC index, ASE, misclassification rate
D. Misclassification rate, ROC index, ASE

Answer: C

NEW QUESTION # 11
Which statement describes the Decision Tree Split Search mechanism for categorical inputs?
Select one:
Response:

A. All levels are weighted and the weights are used for testing.
B. The levels that have target rate of 0 or 100% are re-binned first, then weighted and the weights are used for testing.
C. A clustering mechanism eliminates observations in outlier clusters as potential split points as a first step. Then, for the remaining observations, the average target value is calculated for each level, and then passed on for testing if it is the optimal split point.
D. The average target value is calculated for each level, and then passed on for testing if it is the optimal split point.

Answer: D

NEW QUESTION # 12
Impute the missing values for the variable TLSum using the Tree method. What is the mean of the new variable (with the imputed values)?
Response:

A. less than 19,999.99
B. 30,000-39,999.99
C. 40,000 or higher
D. 20,000-29,999.99

Answer: A

NEW QUESTION # 13
Refer to the exhibit:

The SAS data set credit_customers contains a numeric variable units_sold that holds only the values: 1, 2, 3, 4. Based on the settings provided in the Advanced Advisor Options, what will be the Role and Level of the units_sold variable when the credit_customers data set is created using Advanced Metadata Advisor in the Data Source Wizard?
Select one:
Response:

A. Role: InputLevel: Nominal
B. Role: InputLevel: Interval
C. Role: IntervalLevel: Input
D. Role: RejectedLevel: Nominal

Answer: A

NEW QUESTION # 14
Assume a variable is coded as follows: 1=unmarried, 2=married, 3=divorced, and 4=widowed. Then which of the following measurement levels should be selected in SAS Enterprise Miner for this variable?
Response:

A. Interval
B. Unary
C. Nominal
D. Ordinal

Answer: C

NEW QUESTION # 15
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