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01. Which of the following is not true about results produced by the Regression node?
a) Model Information provides you with information that includes the number of target categories and the number of model parameters.
b) Variable Summary information identifies the roles of variables used by the Regression node.
c) Type 3 Analysis of Effects provides you with information about the number of parameters that each input contributes to the model.
d) Fit Statistics can provide information that affects decision predictions, but does not affect estimate predictions.
02. 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?
a) $0.00
b) $8,711.65
c) $9,586.55
d) $11,142.45
Look over the output from the Neural Network model. Which of the following statement(s) is (are) true?
a) The model has too few input variables.
b) The optimization for the model has not been completed.
c) The misclassification error for the test data is 0.154255.
d) All of the above
04. Which of the following is not a good reason to”regularize” input distributions using a simple transformation?
a) Another benefit is ease in model interpretation.
b) One benefit is improved model performance.
c) When you perform regression, inputs with highly skewed or highly kurtotic distributions can be selected over inputs that would yield better overall predictions.
d) Regression models are sensitive to extreme or outlying values in the input space.
05.
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)?
a) 0.32959
b) 0.42541
c) 0.42667
d) 1.000000
06. 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?
a) 8
b) 12
c) 19
d) 47
07. Which of the following solves problems for you when you impute missing values?
a) When you impute a synthetic value, it replaces missing values with 1 or 0.
b) When you impute a synthetic value, it eliminates the incomplete case problem.
c) When you impute a synthetic value, predictive information is retained.
d) When you impute a synthetic value, each missing value becomes an input to the model.
08.
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 Cubic Clustering Criterion statistic for this clustering?
a) 5.00
b) 14.69
c) 5862.76
d) 67409.93
Multicollinearity in regression refers to which of the following?
a) high correlations among input variables
b) non-normality of the target variable
c) non-constant variance of the target variable
d) high skewness in distributions of input variables
10. Which of the following sequential selection methods do you use so that SAS Enterprise Miner will look at all variables already included in the model and delete any variable that is not significant at the specified level?
a) Backward
b) Forward
c) Stepwise
d) None
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