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| Section | Objectives |
|---|---|
| Topic 1: Model Development | - Neural networks and advanced modeling in SAS Enterprise Miner - Decision trees and ensemble methods - Regression modeling techniques |
| Topic 2: Exploratory Data Analysis | - Descriptive statistics and data profiling - Visualization techniques for pattern discovery |
| Topic 3: Model Evaluation and Validation | - Model performance metrics - Validation and cross-validation techniques - Model comparison and selection |
| Topic 4: Model Implementation and Deployment | - Monitoring model performance in production - Model scoring and deployment in SAS Enterprise Miner |
| Topic 5: Data Understanding and Preparation | - Feature selection and transformation - Data cleaning and preprocessing - Data collection and data source identification - Handling missing values and outliers |
| Topic 6: Business Understanding and Analytical Framework | - Translate business problems into data mining tasks - Define business objectives and analytics goals |
What is the variable worth of the PromCntCardAll variable in Segment 1?
Select one:
Response:
Correct Answer: C 🗳️
The selected model, based on the misclassification rate for the validation data, has how many input variables?
Response:
Correct Answer: B 🗳️
Assume a variable is coded as follows: 1=unmarried, 2=married, 3=divorced, and 4=widowed. Then which of the following measurement levels should be selected in SAS Enterprise Miner for this variable?
Response:
Correct Answer: B 🗳️
Perform these tasks in SAS Enterprise Miner:
- Add a Decision Tree node after the Impute node with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the decision tree to use 1 for Number of Surrogate Rules and Largest for Method in Subtree. Do not change any other property of the Decision Tree node.
- Add another Neural Network node after the decision tree with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the Neural Network model to use Average Error for Model Selection Criterion. Do not change any other property for the Neural Network node. Run the process flow.
How many leaves are there in the decision tree?
Response:
Correct Answer: A 🗳️
Assume that a company has an excellent customer segmentation in place and the segment scheme is a variable in the input data set. What is the best partition method that one should use?
Select one:
Response:
Correct Answer: D 🗳️
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