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SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions:
1. For the Variable Selection node, which statement describes the R-squared variable selection criterion?
Select one:
Response:
A) It uses a squared correlation and then a stepwise regression to eliminate irrelevant inputs.
B) It uses a chi-squared Decision Tree with no Bonferoni adjustment to select the relevant inputs.
C) It looks for a set of colinear inputs that correlate with the target.
D) It is similar to a decision tree algorithm in being able to detect nonlinear and non-additive relationships between inputs and the target.
2. 1. Create a project named Insurance, with a diagram named Explore.
2. Create the data source, DEVELOP, in SAS Enterprise Miner. DEVELOP is in the directory c:\workshop\Practice.
3. Set the role of all variables to Input, with the exception of the Target variable, Ins (1= has insurance, 0= does not have insurance).
4. Set the measurement level for the Target variable, Ins, to Binary.
5. Ensure that Branch and Res are the only variables with the measurement level of Nominal.
6. All other variables should be set to Interval or Binary.
7. Make sure that the default sampling method is random and that the seed is 12345.
The variable Branch has how many levels?
Response:
A) 12
B) 47
C) 8
D) 19
3. 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.
In the training data set, consider only those observations for which the actual value of the target variable equals 1, TARGET=1. What percentage of these observations is being correctly predicted by the decision tree?
Response:
A) 15
B) 14.6216
C) 66.6667
D) 80.3571
4. 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) the average of the absolute values of parameter estimates between the input and all of the hidden neurons
B) none of the above
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
5. An analyst is performing a market basket analysis (affinity analysis) on the purchase of Shaving Cream and Seltzer Water. The purchase data from a set of 250 customers is shown below:
What is the confidence of the rule "Shaving Cream implies Seltzer Water"? You may use a calculator for this question. On the certification exam, an on-screen calculator is provided for you.
Select one:
Response:
A) 67%
B) 57%
C) 60%
D) 40%
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: D | Question # 3 Answer: A | Question # 4 Answer: B | Question # 5 Answer: B |
By Lynn
