Predictive Modeling Using SAS Enterprise Miner 13
Exam Content Guide
Below we provide a list of the objectives that will be tested on the exam.
For more specific details about each objective download the complete exam content guide.

Data Sources
- Create data sources from SAS tables in Enterprise Miner
- Explore and assess data sources
- Modify source data
- Prepare data to be submitted to a predictive model
Building Predictive Models
- Describe key predictive modeling terms and concepts
- Build predictive models using decision trees
- Build predictive models using regression
- Build predictive models using neural networks
Predictive Model Assessment
- Use the correct fit statistic for different prediction types
- Use decision processing to adjust for oversampling (separate sampling)
- Use profit/loss information to assess model performance
- Compare models with the MODEL COMPARISON node
Model Implementation
- Score data sets within Enterprise Miner
- Export score code
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