• Contents
  • About
  • Introduction to SAS Enterprise Miner Software
    • Data Mining Overview
    • Layout of the SAS Enterprise Miner Window
    • Using the Application Main Menus
    • Using the Toolbox
    • Using the Pop-Up Menus
    • Unavailable and Dimmed Items
    • Enterprise Miner Documentation
  • Working with Projects
    • Project Overview
    • Project Directory Structure
    • Viewing and Specifying Project Properties
    • Creating a New Local Project
    • Creating a Client/Server Project
    • Opening a Process Flow Diagram
    • Opening an Existing Project
    • Saving a Project Diagram
    • Running a Project Diagram
    • Closing Projects and Diagrams
    • Creating a New Diagram
    • Deleting Projects and Diagrams
    • Project Troubleshooting Tips
    • Exporting Enterprise Miner 4.3 Projects
    • Opening Enterprise Miner Release 4.2 and Earlier Projects
  • Building Process Flow Diagrams
    • Components Used to Build Process Flow Diagrams
    • Using the Diagram Workspace Pop-up Menu
    • Adding Nodes to a Diagram
    • Using the Node Pop-up Menu
    • Connecting Nodes in a Diagram
    • Cutting Connections in a Diagram
    • Deleting Nodes from a Diagram
    • Moving Nodes in a Diagram
    • Copying and Pasting a Node
    • Cloning a Node
  • Process Flow Diagram Logic
    • Organization of Enterprise Miner Nodes
    • Sampling Nodes
    • Exploring Nodes
    • Modifying Nodes
    • Modeling Nodes
    • Assessing Nodes
    • Scoring Nodes
    • Utility Nodes
    • Subdiagrams
    • Usage Rules for Nodes
  • Common Features among Nodes
    • Functionality
    • Data Tab
    • Variables Tab
    • Notes Tab
    • Results Browser
    • Viewing and Setting Node Defaults
  • Data Structure Examples
    • Types of Data Structures
    • Regression Data
    • Association Discovery Data
  • Example Process Flow Diagram
    • Process Flow Diagram Scenario
    • Task 1. Creating a New Local Project
    • Task 2. Defining the Input Data Set
    • Task 3. Setting the Target Variable
    • Task 4. Defining a Target Profile for the GOOD_BAD Target Variable
    • Task 5. Examining Summary Statistics for the Interval and Class Variables
    • Task 6. Creating Training and Validation Data Sets
    • Task 7. Creating Variable Transformations
    • Task 8. Creating a Stepwise Logistic Regression Model
    • Task 9. Creating a Multilayer Perceptron Neural Network Model
    • Task 10. Creating a Tree Model
    • Task 11. Assessing the Models
    • Task 12. Defining the Score Data Set
    • Task 13. Scoring the Score Data Set
    • Task 14. Viewing the Expected Losses in the Score Data Set
    • Task 15. Creating a Score Card of the Good Credit Risk Applicants
    • Task 16. Closing the Diagram
  • References
    • References
  • Variable Layout for SAMPSIO.DMAGECR (German Credit Data Set)
    • SAMPSIO.DMAGECR (German Credit Data Set)
  • Recommended Reading
  • Glossary


ProductRelease
SAS Enterprise Miner9.1.3
Type
Usage and Reference
Last Updated
01Jun2011