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SASInstitute A00-255 Exam Syllabus Topics:

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

1. The importance of an input variable in predicting a target in an MLP-based neural network can be figured out by which of the following?
Response:

A) none of the above
B) the average of the absolute values of parameter estimates between the input and all of the hidden neurons
C) the highest absolute value of the parameter estimate between the input and any of the hidden neurons
D) the highest absolute value of the parameter estimate between the input and any of the hidden neurons multiplied by the absolute value of the parameter estimate of the hidden neuron

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) Random
B) Stratify
C) Systemic
D) Cluster

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

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

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) 83.1126%
D) 16.8874%

5. The Chi Square statistic for measuring association between the variables BanruptcyInd and TARGET is which of the following?
Response:

A) between 1.00 and 1.99
B) 3.00 or higher
C) less than 1.00
D) between 2.00 and 2.99

Solutions: