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IBM SPSS Modeler Cookbook

IBM SPSS Modeler Cookbook

By : Keith McCormick, Abbott
4.4 (20)
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IBM SPSS Modeler Cookbook

IBM SPSS Modeler Cookbook

4.4 (20)
By: Keith McCormick, Abbott

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 (11 chapters)
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10
Index

Translating your business objective into a data mining objective by Dean Abbott

The business objectives use business language to describe the purpose of the data mining project. However, business objectives are not sufficiently specific to build predictive models; business objectives must be translated into data mining goals. These data mining objectives should be expressed in the language of data mining or data mining software so that the objectives are clear and reproducible.

For example, let's assume the federal government is trying to crack down on government-contracting invoice fraud. A broad business objective may be to identify fraudulent invoices more effectively from the millions of invoices submitted annually. A more specific business objective may be to develop predictive models to identify 100 invoices per month for investigators to examine that are highly likely to be fraudulent.

For the former, the business objective can be to create a data mining objective such as building...

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