A00-255 CERTIFICATION TRAINING: SAS PREDICTIVE MODELING USING SAS ENTERPRISE MINER 14 & A00-255 STUDY GUIDE & A00-255 EXAM BOOTCAMP

A00-255 Certification Training: SAS Predictive Modeling Using SAS Enterprise Miner 14 & A00-255 Study Guide & A00-255 Exam Bootcamp

A00-255 Certification Training: SAS Predictive Modeling Using SAS Enterprise Miner 14 & A00-255 Study Guide & A00-255 Exam Bootcamp

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SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions (Q81-Q86):

NEW QUESTION # 81
Multicollinearity in regression refers to which of the following?
Response:

  • A. non-constant variance of the target variable
  • B. high correlations among input variables
  • C. non-normality of the target variable
  • D. high skewness in distributions of input variables

Answer: B


NEW QUESTION # 82
Choose the correct statement that illustrates Decision Tree Split Search for continuous (interval) inputs:
Select one:
Response:

  • A. The variable goes through a non-linear transformation, and the transformed variable is used for testing.
  • B. Each unique value has the potential of being the optimal split point.
  • C. Each unique value has the potential of being the optimal split point, except for the extreme observation.
  • D. The variable goes through a binning process, the bins are weighted based on the proportion of events in each bin, and then finally tested as an optimal split point.

Answer: B


NEW QUESTION # 83
1. Define a new data source, PatternData, in SAS Enterprise Miner (SAS data set Patterndata.sas7bdat in the zip file distributed with this practice exam).
2. Set the role of all variables to Input, with the exception set the ID variable role to ID.
3. Set the measurement level for all variables to Interval, except:
- Set DemHomeOwner and StatusCatStarAll to Binary.
- Set DemCluster, DemGender, ID, and StatusCat96NK to Nominal.
4. Create a new diagram (name it Section6) within the project labeled Test.
5. Add the data source, PatternData, to this diagram. Make sure the variable roles and measurements are the same as in the table below. (Check the highlighted rows carefully and reset roles/levels as needed.)
6. Connect a Cluster node to the data source.
7. Modify the Cluster node to exclude nominal and binary input variables.
8. Run the Cluster node.

How many clusters are created by the Cluster node?
Response:

  • A. 0
  • B. 1
  • C. 2
  • D. 3

Answer: D


NEW QUESTION # 84
Transformation of input variables to make their distributions more symmetric will likely have what impact in a logistic regression?
Select one:
Response:

  • A. create convergence problems in maximum likelihood estimation
  • B. decrease the performance of logistic regression
  • C. neither increase nor decrease the performance of logistic regression
  • D. increase the performance of logistic regression

Answer: D


NEW QUESTION # 85
How many unique indicator variables were created during imputation?
Response:

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

Answer: B


NEW QUESTION # 86
......

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