Exam Code: A00-225
Exam Name: SAS Advanced Predictive Modeling
Updated: Sep 13, 2026
Q & A: 0 Questions and Answers
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| Section | Objectives |
|---|---|
| Data Exploration and Preparation | - Data cleaning, missing value handling, and transformations - Feature selection and variable reduction techniques |
| Model Deployment Concepts | - Scoring data and operationalizing models |
| Model Assessment and Validation | - Lift charts, ROC curves, and confusion matrix - Model comparison and selection strategies |
| Clustering and Segmentation | - K-means clustering and hierarchical clustering |
| SEMMA Methodology and Enterprise Miner Environment | - Understanding SEMMA process (Sample, Explore, Modify, Model, Assess) - SAS Enterprise Miner project workflow and nodes |
| Predictive Modeling Techniques | - Neural networks and ensemble methods - Decision trees and rule-based models - Regression models (linear and logistic regression) |
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