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

1. Refer to the exhibit:

When the Explore button is selected in the graphic, what information will be displayed?
Select one:
Response:

A) Sample Properties, Sample Statistics, sample data for the selected variable, and a histogram of the data for the selected variable
B) Sample Properties, Sample Statistics, sample data for the selected variable, and a pie chart of the selected variable
C) Sample Properties, Sample Statistics for all variables, and sample data for all variables
D) Sample Properties, Sample Statistics, sample data with all variables and values, and a histogram of the data for the selected variable

2. 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 is the probability that TARGET=0 for ID=000355 in the training data?
Response:

A) 0.077935227
B) 0.9220647773
C) 0.0658174098
D) 0.9341825902

3. 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 multiplied by the absolute value of the parameter estimate of the hidden neuron
D) the highest absolute value of the parameter estimate between the input and any of the hidden neurons

4. If the bank wanted to select the best model based on the models' overall performances on the validation data as measured by the average squared error, then the best model is which of the following?
Response:

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

5. Which model was picked as the best model by SAS Enterprise Miner?
Response:

A) Decision Tree (3-way)
B) None of the above
C) Decision Tree
D) Regression

Solutions: