Predictive Modeling Using SAS Enterprise Miner 14

Exam Content Guide

During the testing of these objectives;
You will be expected to perform common tasks, such as:

• Create a new project in Enterprise Miner
• Open an existing project in Enterprise Miner
• Add diagrams to projects in Enterprise Miner
• Create libraries within Enterprise Miner
• Add nodes to diagrams in Enterprise Miner
• Copy nodes within Enterprise Miner
• Connect nodes to create process flows in Enterprise Miner
• Change interactive sampling methods for data exploration
• Work with the Help functionality within Enterprise Miner

Data Sources - 20-25%

• 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 - 35-40%

• 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 and Implementation - 25-30%

• 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
• Score data sets within Enterprise Miner

Pattern Analysis - 10-15%   (new content)

• Identify clusters of similar data with the CLUSTER and SEGMENT PROFILE nodes
• Perform association and sequence analysis (market basket analysis)