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

Removing fields with the Filter node

Whereas the Select node works on records, the Filter node works on fields. The Filter node discards fields, renames fields, and maps fields from one source node to another. Often, a Filter node is used to remove fields that have one of two potential problems:

  • A large proportion of missing records
  • All (or almost all) records having the same value

In our case, we have two fields that have a large portion of missing values, therefore we will remove these fields:

  1. Place a Filter node from the Field Ops palette to the right of the Append node.
  2. Connect the Append node to the Filter node.
  3. Right-click the Filter node, then click Edit.

The Filter node (or Filter tab of a source node) allows data to pass through it and has two main functions:

  • Removing unwanted fields
  • Renaming fields

The left column of a Filter node lists the field names as the data enters the node. The right column of a Filter node shows the field names as the data leaves the node. By default, the lists are...