Decision Trees for Analytics Using SAS Enterprise Miner

Chapter 3: The Mechanics of Decision Tree Construction

The Basics of Decision Trees

Step 1—Preprocess the Data for the Decision Tree Growing Engine

Step 2—Set the Input and Target Modeling Characteristics

Targets

Inputs

Step 3—Select the Decision Tree Growth Parameters

Step 4—Cluster and Process Each Branch-Forming Input Field

Clustering Algorithms

The Kass Merge-and-Split Heuristic

Dealing with Missing Data and Missing Inputs in Decision Trees

Step 5—Select the Candidate Decision Tree Branches

Step 6—Complete the Form and Content of the Final Decision Tree

Switching Targets

Example of Multiple Target Selection Using the Home Equity Demonstration Data

Synergy, Functionality, and the Wisdom of the End User

The Basics of Decision Trees

The goal ...