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IBM SPSS Modeler Essentials (Paperback)
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IBM SPSS Modeler Essentials (Paperback)
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Get to grips with the fundamentals of data mining and predictive
analytics with IBM SPSS Modeler About This Book * Get
up-and-running with IBM SPSS Modeler without going into too much
depth. * Identify interesting relationships within your data and
build effective data mining and predictive analytics solutions * A
quick, easy-to-follow guide to give you a fundamental understanding
of SPSS Modeler, written by the best in the business Who This Book
Is For This book is ideal for those who are new to SPSS Modeler and
want to start using it as quickly as possible, without going into
too much detail. An understanding of basic data mining concepts
will be helpful, to get the best out of the book. What You Will
Learn * Understand the basics of data mining and familiarize
yourself with Modeler's visual programming interface * Import data
into Modeler and learn how to properly declare metadata * Obtain
summary statistics and audit the quality of your data * Prepare
data for modeling by selecting and sorting cases, identifying and
removing duplicates, combining data files, and modifying and
creating fields * Assess simple relationships using various
statistical and graphing techniques * Get an overview of the
different types of models available in Modeler * Build a decision
tree model and assess its results * Score new data and export
predictions In Detail 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. Style and approach This book empowers users to build
practical & accurate predictive models quickly and intuitively.
With the support of the advanced analytics users can discover
hidden patterns and trends.This will help users to understand the
factors that influence them, enabling you to take advantage of
business opportunities and mitigate risks.
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