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SASInstitute A00-255 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Data Understanding and Preparation | - Data cleaning and preprocessing - Feature selection and transformation - Data collection and data source identification - Handling missing values and outliers |
| Model Evaluation and Validation | - Validation and cross-validation techniques - Model comparison and selection - Model performance metrics |
| Model Implementation and Deployment | - Model scoring and deployment in SAS Enterprise Miner - Monitoring model performance in production |
| Business Understanding and Analytical Framework | - Translate business problems into data mining tasks - Define business objectives and analytics goals |
| Exploratory Data Analysis | - Visualization techniques for pattern discovery - Descriptive statistics and data profiling |
| Model Development | - Decision trees and ensemble methods - Neural networks and advanced modeling in SAS Enterprise Miner - Regression modeling techniques |
SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions:
Look over the output from the Neural Network model. Which of the following statement(s) is (are) true?
Response:
- A. The optimization for the model has not been completed.
- B. The model has too few input variables.
- C. All of the above
- D. The misclassification error for the test data is 0.154255.
Correct Answer: A 🗳️
Multicollinearity in regression refers to which of the following?
Response:
- A. high correlations among input variables
- B. high skewness in distributions of input variables
- C. non-constant variance of the target variable
- D. non-normality of the target variable
Correct Answer: A 🗳️
For the variable InqCnt06, replace all values over 10.1 with the value 10. How many values are replaced?
Response:
- A. 200 or higher
- B. 0-99
- C. 150-199
- D. 100-149
Correct Answer: D 🗳️
If the bank wanted to select the best model based on the models' overall performances on the validation data as measured by the average squared error, then the best model is which of the following?
Response:
- A. Decision Tree
- B. Neural Network
- C. Decision Tree (3-way)
- D. Regression
Correct Answer: D 🗳️
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?
Response:
- A. Forward
- B. None
- C. Backward
- D. Stepwise
Correct Answer: B 🗳️
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