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

1. Which of the following is not a good reason to"regularize" input distributions using a simple transformation?
Response:

A) One benefit is improved model performance.
B) When you perform regression, inputs with highly skewed or highly kurtotic distributions can be selected over inputs that would yield better overall predictions.
C) Regression models are sensitive to extreme or outlying values in the input space.
D) Another benefit is ease in model interpretation.

2. Which method of input selection for regression analysis evaluates the statistical significance of all included inputs after each input is added?
Select one:
Response:

A) Backward
B) Forward
C) Stepwise
D) Simple

3. For the variable TLCnt24, apply a Max Normal transformation. What transformation was selected by SAS Enterprise Miner?
Response:

A) Square
B) Square Root
C) Log
D) Exponential

4. 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.
What percentage of all observations is being correctly predicted in the test data set by the decision tree?
Response:

A) 85.2222%
B) 84.5212%
C) 16.8874%
D) 83.1126%

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

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

Solutions: