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

Combining data files with the Merge node

In many organizations, different pieces of information for the same individuals are held in separate locations. To be able to analyze such information within Modeler, the data files must be combined into one single file. The Merge node joins two or more data sources so that information held for an individual in different locations can be analyzed collectively. The following diagram shows how the Merge node can be used to combine two separate data files that contain different types of information:

Like the Append node, the Merge node is found in the Record Ops palette. This node takes multiple data sources and creates a single source containing all or some of the input fields.

Let's go through an example of how to use the Merge node to combine data files:

  1. Open the Merge stream.

The Merge stream contains the files we previously appended, as well as the main data file we were working with in earlier chapters.

  1. Place a Merge node from the Record Ops palette...