Predictive Modeling Using SAS Enterprise Miner 13

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