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| Section | Objectives |
|---|---|
| Model Implementation and Deployment | - Monitoring model performance in production - Model scoring and deployment in SAS Enterprise Miner |
| Business Understanding and Analytical Framework | - Define business objectives and analytics goals - Translate business problems into data mining tasks |
| Model Development | - Neural networks and advanced modeling in SAS Enterprise Miner - Decision trees and ensemble methods - Regression modeling techniques |
| Exploratory Data Analysis | - Visualization techniques for pattern discovery - Descriptive statistics and data profiling |
| Model Evaluation and Validation | - Model comparison and selection - Validation and cross-validation techniques - Model performance metrics |
| Data Understanding and Preparation | - Data cleaning and preprocessing - Data collection and data source identification - Handling missing values and outliers - Feature selection and transformation |
Question 1
Multicollinearity in regression refers to which of the following?
Response:
A. non-constant variance of the target variable
B. high correlations among input variables
C. high skewness in distributions of input variables
D. non-normality of the target variable
Question 2
What is the purpose of the Kass (Bonferroni) adjustment in the decision tree split-search algorithm?
Select one:
Response:
A. To give categorical inputs a greater chance to be used the split.
B. To ensure that the choice of split is not influenced by input measurement scale.
C. To reduce the number of surrogate splitting rules.
D. To ensure a non-negative logworth value.
Question 3
Choose the correct statement that illustrates Decision Tree Split Search for continuous (interval) inputs:
Select one:
Response:
A. The variable goes through a non-linear transformation, and the transformed variable is used for testing.
B. Each unique value has the potential of being the optimal split point.
C. Each unique value has the potential of being the optimal split point, except for the extreme observation.
D. The variable goes through a binning process, the bins are weighted based on the proportion of events in each bin, and then finally tested as an optimal split point.
Question 4
For the variable InqTimeLast, which term best describes the shape of its distribution?
Response:
A. symmetric
B. bimodal
C. right skewed
D. left skewed
Question 5
What is the number of missing values for the TLSum variable in the sample generated by SAS Enterprise Miner?
Response:
A. 40 or more
B. 20-39
C. 1-19
D. 0
Solutions:
| Question 1 Answer: B | Question 2 Answer: B | Question 3 Answer: B | Question 4 Answer: C | Question 5 Answer: A |
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