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SASInstitute A00-255 Exam Syllabus Topics:

SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions:

1. For an ordinal variable with L levels, the number of possible splits in a decision tree is which of the following?
Response:

A) 2L-1-1
B) 2L
C) (L-1)/1
D) 2L-1

2. For the Variable Selection node, which statement describes the R-squared variable selection criterion?
Select one:
Response:

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

3. If the bank wanted to select the best model based on which model achieves the highest lift for the third decile in the validation data, then which of the following is the best model?
Response:

A) Neural Network
B) Decision Tree (3-way)
C) Decision Tree
D) Regression

4. What is the purpose of the Kass (Bonferroni) adjustment in the decision tree split-search algorithm?
Select one:
Response:

A) To reduce the number of surrogate splitting rules.
B) To ensure a non-negative logworth value.
C) To ensure that the choice of split is not influenced by input measurement scale.
D) To give categorical inputs a greater chance to be used the split.

5. Perform these tasks in SAS Enterprise Miner:
- Use the Regression node to build another regression model with TARGET as the dependent variable and all other input variables as independent variables (main effects only).
- Configure the regression model to use Stepwise for Selection Model and Validation Error for Selection Criteri a. Do not change any other property for the regression model.
For the validation data, in what range does cumulative percent captured response at the 60th percentile lie?
Response:

A) 0-24.99
B) 50-74.99
C) 25-49.99
D) 75 or more

Solutions: