SASInstitute A00-255 actual dump : SAS Predictive Modeling Using SAS Enterprise Miner 14

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SASInstitute A00-255 Exam Syllabus Topics:

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

1. 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.
What is the mean credit card balance (CCBal) of the customers with a variable annuity?
Response:

A) $8,711.65
B) $0.00
C) $9,586.55
D) $11,142.45

2. Open the diagram labeled Practice A within the project labeled Practice A. Perform the following in SAS Enterprise Miner:

1. Set the Clustering method to Average.
2. Run the Cluster node.
What is the Importance statistic for MTGBal (Mortgage Balance)?
Response:

A) 0.42541
B) 0.42667
C) 0.32959
D) 0.60485

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 decision tree model, what is the importance of the variable InqCnt06?
Response:

A) less than 0.149999
B) 0.30-0.449999
C) 0.15-0.299999
D) 0.45 or higher

4. Multicollinearity in regression refers to which of the following?
Response:

A) high skewness in distributions of input variables
B) non-normality of the target variable
C) non-constant variance of the target variable
D) high correlations among input variables

5. Assume in a data mining project that the task is to predict rankings of a target variable as accurately as possible. Which of the following should be used to judge prediction models?
Response:

A) KS statistic
B) Gini coefficient
C) average squared error
D) misclassification

Solutions: