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New SASInstitute A00-255 Exam Test | Exam A00-255 Pass Guide

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Posted on: 02/22/25

With a vast knowledge in the field, Pass4SureQuiz is always striving hard to provide actual, authentic SASInstitute Exam Questions so that the candidates can pass their SAS Predictive Modeling Using SAS Enterprise Miner 14 (A00-255) exam in less time. Pass4SureQuiz tries hard to provide the best SAS Predictive Modeling Using SAS Enterprise Miner 14 (A00-255) dumps to reduce your chances of failure in the SAS Predictive Modeling Using SAS Enterprise Miner 14 (A00-255) exam. Pass4SureQuiz provides an exam scenario with its SASInstitute A00-255 practice test (desktop and web-based) so the preparation of the SAS Predictive Modeling Using SAS Enterprise Miner 14 (A00-255) exam questions becomes quite easier.

SASInstitute A00-255 Certification Exam is designed for professionals who want to gain expertise in predictive modeling using SAS Enterprise Miner 14. A00-255 exam is ideal for data analysts, statisticians, and data miners who want to enhance their skills in predictive modeling and data analysis using SAS Enterprise Miner. A00-255 exam is also suitable for individuals who want to demonstrate their knowledge and expertise in SAS predictive modeling to potential employers.

SASInstitute A00-255 Certification Exam is a rigorous and challenging exam that requires a thorough understanding of predictive modeling concepts and techniques. A00-255 exam consists of multiple-choice questions and is timed for two hours. Candidates must achieve a passing score of 70% or higher to earn the certification. A00-255 exam is available in several languages, including English, Chinese, and Japanese.

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Exam A00-255 Pass Guide | New A00-255 Exam Questions

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The main objectives of the SAS Institute A00-255: SAS Predictive Modeling Using SAS Enterprise Miner 14 exam include understanding the key principles of predictive modelling, learning about the SAS Enterprise Miner interface, and mastering concepts such as data manipulation, variable selection, data exploration, and data partitioning. An individual appearing for A00-255 Exam should have a good understanding of statistical techniques and data analytics, as these skills are crucial to excel in the field of predictive modelling.

SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions (Q15-Q20):

NEW QUESTION # 15
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. TLDel90Cnt24
  • B. InqFinanceCnt24.
  • C. TLDel3060Cnt24
  • D. IMP_TLSatCnt

Answer: C


NEW QUESTION # 16
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.
How many leaves are there in the decision tree?
Response:

  • A. 1-10
  • B. 16-20
  • C. 11-15
  • D. 21 or more

Answer: C


NEW QUESTION # 17
Suppose your input variables have missing values. Before running a decision tree with these input variables, you should do which of the following?
Response:

  • A. impute all missing values using the Tree method
  • B. not impute any missing values because trees can handle them.
  • C. impute only class variables using the Tree method but do not impute the interval variables
  • D. impute only interval variables using the Tree method but do not impute the class variables

Answer: B


NEW QUESTION # 18
Sometimes in predictive modeling we build models using a sample that has a primary outcome proportion different from true population proportion. This is usually done when the ratio of primary to secondary outcomes in a binary target variable in the population is close to which of the following?
Response:

  • A. 0.05
  • B. 0
  • C. 1.2
  • D. 0.8

Answer: A


NEW QUESTION # 19
Refer to the exhibit:

What would be the decision threshold (probability cutoff) generated for this decision matrix. You may use a calculator for this question. On the certification exam, an on-screen calculator is provided for you.
Select one:
Response:

  • A. 0.82
  • B. 0.18
  • C. 0.21
  • D. 0.27

Answer: B


NEW QUESTION # 20
......

Exam A00-255 Pass Guide: https://www.pass4surequiz.com/A00-255-exam-quiz.html

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