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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