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SASInstitute A00-255 (SAS Predictive Modeling Using SAS Enterprise Miner 14) certification exam is designed for professionals who want to demonstrate their expertise in predictive modeling using SAS Enterprise Miner 14. SAS Institute is a well-known software company that provides analytics and data management solutions. SAS Enterprise Miner is one of their flagship products that allows users to build predictive models using advanced analytics techniques.

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SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions (Q50-Q55):

NEW QUESTION # 50
For the Variable Selection node, which statement describes the R-squared variable selection criterion?
Select one:
Response:

A. It uses a chi-squared Decision Tree with no Bonferoni adjustment to select the relevant inputs.
B. It looks for a set of colinear inputs that correlate with the target.
C. It uses a squared correlation and then a stepwise regression to eliminate irrelevant inputs.
D. It is similar to a decision tree algorithm in being able to detect nonlinear and non-additive relationships between inputs and the target.

Answer: C

NEW QUESTION # 51
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. 40,000 or higher
B. 30,000-39,999.99
C. less than 19,999.99
D. 20,000-29,999.99

Answer: C

NEW QUESTION # 52
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 # 53
Perform these tasks in SAS Enterprise Miner:
Add a Decision Tree node, as shown below. (Make sure you use only default options in the Decision Tree node.)

Run the Decision Tree node.
Suppose that the data has been oversampled and the probability that TARGET=1 is 0.10 in the population. Incorporate the above scenario and run the Decision Tree node again.
What is the misclassification rate in the validation data set?
Response:

A. 0.10
B. 0.154788
C. 0.162252
D. 0.157016

Answer: D

NEW QUESTION # 54
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 # 55
......

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