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SASInstitute A00-255 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Data Understanding and Preparation | - Feature selection and transformation - Handling missing values and outliers - Data cleaning and preprocessing - Data collection and data source identification |
| Model Development | - Regression modeling techniques - Neural networks and advanced modeling in SAS Enterprise Miner - Decision trees and ensemble methods |
| Model Implementation and Deployment | - Monitoring model performance in production - Model scoring and deployment in SAS Enterprise Miner |
| Exploratory Data Analysis | - Visualization techniques for pattern discovery - Descriptive statistics and data profiling |
| Model Evaluation and Validation | - Model performance metrics - Model comparison and selection - Validation and cross-validation techniques |
| Business Understanding and Analytical Framework | - Translate business problems into data mining tasks - Define business objectives and analytics goals |
SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions:
Question 1
Which model was picked as the best model by SAS Enterprise Miner?
Response:
A. None of the above
B. Decision Tree
C. Regression
D. Decision Tree (3-way)
Question 2
Which method of input selection for regression analysis evaluates the statistical significance of all included inputs after each input is added?
Select one:
Response:
A. Forward
B. Backward
C. Stepwise
D. Simple
Question 3
Sometimes in predictive modeling we build models using a sample that has a primary outcome proportion different from true population proportion. This is usually done when the ratio of primary to secondary outcomes in a binary target variable in the population is close to which of the following?
Response:
A. 1
B. 0.05
C. 1.2
D. 0.8
Question 4
A useful concept in logistic regression is the doubling amount. How would you calculate doubling amount for an input variable that has a parameter estimate of b1?
Response:
A. 2/log(b1)
B. 2*log(b1)
C. 2*b1
D. 0.69/b1
Question 5
The number of hidden layers in this Neural Network model is which of the following?
Response:
A. 1
B. 4 or more
C. 2
D. 3
Solutions:
| Question 1 Answer: B | Question 2 Answer: C | Question 3 Answer: B | Question 4 Answer: D | Question 5 Answer: A |
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