Book Image

IBM SPSS Modeler Essentials

By : Jesus Salcedo, Keith McCormick
Book Image

IBM SPSS Modeler Essentials

By: Jesus Salcedo, Keith McCormick

Overview of this book

IBM SPSS Modeler allows users to quickly and efficiently use predictive analytics and gain insights from your data. With almost 25 years of history, Modeler is the most established and comprehensive Data Mining workbench available. Since it is popular in corporate settings, widely available in university settings, and highly compatible with all the latest technologies, it is the perfect way to start your Data Science and Machine Learning journey. This book takes a detailed, step-by-step approach to introducing data mining using the de facto standard process, CRISP-DM, and Modeler’s easy to learn “visual programming” style. You will learn how to read data into Modeler, assess data quality, prepare your data for modeling, find interesting patterns and relationships within your data, and export your predictions. Using a single case study throughout, this intentionally short and focused book sticks to the essentials. The authors have drawn upon their decades of teaching thousands of new users, to choose those aspects of Modeler that you should learn first, so that you get off to a good start using proven best practices. This book provides an overview of various popular data modeling techniques and presents a detailed case study of how to use CHAID, a decision tree model. Assessing a model’s performance is as important as building it; this book will also show you how to do that. Finally, you will see how you can score new data and export your predictions. By the end of this book, you will have a firm understanding of the basics of data mining and how to effectively use Modeler to build predictive models.
Table of Contents (19 chapters)
Title Page
About the Authors
About the Reviewer
Customer Feedback

Introducing the Modeler graphic user interface

IBM SPSS Modeler can be thought of as a data mining workbench that combines multiple tools and technologies to support the data mining process. Modeler allows users to mine data visually on the stream canvas.

The following figure shows the different areas of the Modeler interface:

As you can see, the Modeler interface is comprised of several components, and these are described in the next few pages.

Stream canvas

The stream canvas is the main work area in Modeler. It is located in the center of the Modeler user interface. The stream canvas can be thought of as a surface on which to place icons or nodes. These nodes represent operations to be carried out on the data. Once nodes have been placed on the stream canvas, they can be linked together to form a stream.


Nodes (operations on the data) are contained in palettes. The palettes are located at the bottom of the Modeler user interface. Each palette contains a group of related nodes that are...