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SASInstitute A00-255 Exam Syllabus Topics:

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

1. How many unique indicator variables were created during imputation?
Response:

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

2. Consider a binary target variable. Assume Accuracy is the desired assessment measure. Accuracy is not an option in the Decision Tree node. Which assessment measure can you use as a proxy for accuracy?
Select one:
Response:

A) Total Profit
B) Mean Square Error
C) 1 - Misclassification Rate
D) Average Squared Error

3. What is the number of missing values for the TLSum variable in the sample generated by SAS Enterprise Miner?
Response:

A) 0
B) 1-19
C) 40 or more
D) 20-39

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

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

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

Solutions: