PASS GUARANTEED 2025 A00-255: SAS PREDICTIVE MODELING USING SAS ENTERPRISE MINER 14–THE BEST PRACTICE EXAM PDF

Pass Guaranteed 2025 A00-255: SAS Predictive Modeling Using SAS Enterprise Miner 14–The Best Practice Exam Pdf

Pass Guaranteed 2025 A00-255: SAS Predictive Modeling Using SAS Enterprise Miner 14–The Best Practice Exam Pdf

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Tags: Practice A00-255 Exam Pdf, A00-255 Lead2pass, A00-255 Valid Test Review, Valid Braindumps A00-255 Free, A00-255 Latest Exam Question

The SASInstitute A00-255 desktop practice exam software simulates a real test environment and familiarizes you with the actual test format. This SASInstitute A00-255 practice exam software tracks your progress and performance, allowing you to see how much you've improved over time. We frequently update the SASInstitute A00-255 Practice Exam software with the latest SASInstitute A00-255 DUMPS PDF.

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.

SASInstitute A00-255 (SAS Predictive Modeling Using SAS Enterprise Miner 14) exam is designed for professionals who want to demonstrate their abilities in predictive modeling using SAS Enterprise Miner 14. A00-255 Exam measures the candidate's ability to use SAS Enterprise Miner to perform data exploration, variable selection, data preparation, and model assessment. Additionally, the exam tests the candidate's knowledge of SAS programming techniques and statistical analyses.

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SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions (Q41-Q46):

NEW QUESTION # 41
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.
In the validation data, the lift corresponding to the fourth decile is in which of the following ranges?
Response:

  • A. 1.25-.49999
  • B. 0-1.24999
  • C. 1.75 or more
  • D. 1.5-1.74999

Answer: D


NEW QUESTION # 42
Assume the Target has an event proportion of 2% in the original data. Which of the following property values should be used in the Sample node of SAS Enterprise Miner to create a sample from that data with a balanced 50/50 split for Target?
Select one:
Response:

  • A. Sample Method: Stratify and Criterion: Proportional
  • B. Sample Method: Random and Criterion: Proportional
  • C. Sample Method: Stratify and Criterion: Equal
  • D. Sample Method: Random and Criterion: Equal

Answer: C


NEW QUESTION # 43
A useful concept in logistic regression is the doubling amount. How would you calculate doubling amount for an input variable that has a parameter estimate of b1?
Response:

  • A. 2*b1
  • B. 2*log(b1)
  • C. 0.69/b1
  • D. 2/log(b1)

Answer: C


NEW QUESTION # 44
Perform this task using SAS Enterprise Miner:
Continue to use the same diagram. Use an Ensemble node (configure using default options) in SAS Enterprise Miner to combine all four models.
Compare the performance of the ensemble and the four models using average squared error in the validation data. Which is the best model in this comparison?
Response:

  • A. Regression
  • B. Neural Network
  • C. Decision Tree
  • D. Ensemble

Answer: D


NEW QUESTION # 45
Assume that a company has an excellent customer segmentation in place and the segment scheme is a variable in the input data set. What is the best partition method that one should use?
Select one:
Response:

  • A. Stratify
  • B. Cluster
  • C. Random
  • D. Systemic

Answer: A


NEW QUESTION # 46
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