Book Image

IBM SPSS Modeler Cookbook

Book Image

IBM SPSS Modeler Cookbook

Overview of this book

IBM SPSS Modeler is a data mining workbench that enables you to explore data, identify important relationships that you can leverage, and build predictive models quickly allowing your organization to base its decisions on hard data not hunches or guesswork. IBM SPSS Modeler Cookbook takes you beyond the basics and shares the tips, the timesavers, and the workarounds that experts use to increase productivity and extract maximum value from data. The authors of this book are among the very best of these exponents, gurus who, in their brilliant and imaginative use of the tool, have pushed back the boundaries of applied analytics. By reading this book, you are learning from practitioners who have helped define the state of the art. Follow the industry standard data mining process, gaining new skills at each stage, from loading data to integrating results into everyday business practices. Get a handle on the most efficient ways of extracting data from your own sources, preparing it for exploration and modeling. Master the best methods for building models that will perform well in the workplace. Go beyond the basics and get the full power of your data mining workbench with this practical guide.
Table of Contents (17 chapters)
IBM SPSS Modeler Cookbook
Credits
Foreword
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Evaluating balancing with Auto Classifier


Two traps to avoid in data mining are that one should always balance, or that there is only one way to balance. Like most questions asked during a data mining project, the question of whether to balance or not should be answered empirically. The purpose of this recipe is to show how three common kinds of balancing can be compared easily using the Auto Classifier node. This is not to suggest that the resulting models are final models. Rather, this is an early test that can be conducted to evaluate whether or not to balance. One of the kinds of balancing suggested here is to not balance at all. Another suggestion is to double the numbers in a fully reduced balance node.

Getting ready

We will start with the Choose Balance.str stream.

How to do it...

To show how three common kinds of balancing can be compared easily using the Auto Classifier Node:

  1. Open the starting stream.

  2. Edit the Balance node labeled Fully Reduce. This node was automatically generated by...