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SASInstitute A00-255 Exam Syllabus Topics:

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

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

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

2. 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) 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
C) none of the above
D) the highest absolute value of the parameter estimate between the input and any of the hidden neurons

3. Which statement describes the Decision Tree Split Search mechanism for categorical inputs?
Select one:
Response:

A) The average target value is calculated for each level, and then passed on for testing if it is the optimal split point.
B) A clustering mechanism eliminates observations in outlier clusters as potential split points as a first step. Then, for the remaining observations, the average target value is calculated for each level, and then passed on for testing if it is the optimal split point.
C) The levels that have target rate of 0 or 100% are re-binned first, then weighted and the weights are used for testing.
D) All levels are weighted and the weights are used for testing.

4. Perform these tasks in SAS Enterprise Miner:
- Use the Regression node to build another regression model with TARGET as the dependent variable and all other input variables as independent variables (main effects only).
- Configure the regression model to use Stepwise for Selection Model and Validation Error for Selection Criteri a. Do not change any other property for the regression model.
For the validation data, in what range does cumulative percent captured response at the 60th percentile lie?
Response:

A) 0-24.99
B) 50-74.99
C) 25-49.99
D) 75 or more

5. If you only consider observations for which TARGET=0, what percentage of such observations has BanruptcyInd=1?
Response:

A) 80% or higher
B) between 50%-79.99%
C) between 15%-49.99%
D) less than 15%

Solutions: