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IBM SPSS Modeler Essentials

You're reading from IBM SPSS Modeler Essentials

Product type Book

Published in Dec 2017

Publisher Packt

ISBN-13 9781788291118

Pages 238 pages

Edition 1st Edition

Languages

Concepts

Predictive Analytics

Authors (2):

Jesus Salcedo

Keith McCormick

View More author details

Table of Contents (19) Chapters

Title Page

Credits

About the Authors

About the Reviewer

www.PacktPub.com

Customer Feedback

Dedication

Preface

1. Introduction to Data Mining and Predictive Analytics

2. The Basics of Using IBM SPSS Modeler

3. Importing Data into Modeler

4. Data Quality and Exploration

5. Cleaning and Selecting Data

6. Combining Data Files

7. Deriving New Fields

8. Looking for Relationships Between Fields

9. Introduction to Modeling Options in IBM SPSS Modeler

10. Decision Tree Models

11. Model Assessment and Scoring

Summary

This chapter introduced the Derive node. The Derive node can perform many different types of calculations so that users can extract more information from the data. These additional fields can then provide insight that may not have been apparent. In this chapter you learned that the Derive node can create fields as formulas, flags, nominals, or conditionals.

In the next chapter, we will continue to explore our data by discovering simple relationships between outcome fields and predictor fields. Specifically, readers will learn to use several statistical and graphing nodes to determine which fields are related to an outcome variable.

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Authors (2)

Jesus Salcedo

Jesus Salcedo has a PhD in psychometrics from Fordham University. He is an independent statistical consultant and has been using SPSS products for over 20 years. He is a former SPSS Curriculum Team Lead and Senior Education Specialist who has written numerous SPSS training courses and trained thousands of users.

See other products by Jesus Salcedo

Keith McCormick

Keith McCormick is a career long practitioner of predictive analytics and data science. He has engaged in statistical modeling, data mining, and mentoring others in the area for more than 20 years. He has a particular expertise in helping organizations perform their first predictive analytics project or build their first predictive analytics practice, and has done so in a variety of industries including healthcare, banking, telecommunications, non-profit, direct mail, pharmaceuticals, and retail. Keith is also an established author and speaker with four books in print, or under contract. Although his consulting work is not restricted to any one tool, his writing and speaking has made him particularly well known in the IBM SPSS Statistics and IBM SPSS Modeler communities.

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