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

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

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

2. Assume that a company has an excellent customer segmentation in place and the segment scheme is a variable in the input data set. What is the best partition method that one should use?
Select one:
Response:

A) Systemic
B) Cluster
C) Random
D) Stratify

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

4. What percentage of observations in the test data has TARGET=1?
Response:

A) 83.3333
B) 16.5924
C) 16.8874
D) 16.6627

5. Which of the following solves problems for you when you impute missing values?
Response:

A) When you impute a synthetic value, it replaces missing values with 1 or 0.
B) When you impute a synthetic value, predictive information is retained.
C) When you impute a synthetic value, it eliminates the incomplete case problem.
D) When you impute a synthetic value, each missing value becomes an input to the model.

Solutions: