Overview
- Authors:
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David L. Olson
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Department of Management Science, University of Nebraska, Lincoln, USA
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Dursun Delen
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Department of Management, Science and Information Systems, Tulsa, USA
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Table of contents (10 chapters)
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Introduction
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- David L. Olson, Dursun Delen
Pages 3-8
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- David L. Olson, Dursun Delen
Pages 9-35
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Data Mining Methods As Tools
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- David L. Olson, Dursun Delen
Pages 39-52
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- David L. Olson, Dursun Delen
Pages 53-68
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- David L. Olson, Dursun Delen
Pages 69-86
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- David L. Olson, Dursun Delen
Pages 87-109
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- David L. Olson, Dursun Delen
Pages 111-123
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- David L. Olson, Dursun Delen
Pages 125-135
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- David L. Olson, Dursun Delen
Pages 137-147
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Applications
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Front Matter
Pages 149-149
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- David L. Olson, Dursun Delen
Pages 151-167
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Back Matter
Pages 169-180
About this book
The intent of this book is to describe some recent data mining tools that have proven effective in dealing with data sets which often involve unc- tain description or other complexities that cause difficulty for the conv- tional approaches of logistic regression, neural network models, and de- sion trees. Among these traditional algorithms, neural network models often have a relative advantage when data is complex. We will discuss methods with simple examples, review applications, and evaluate relative advantages of several contemporary methods. Book Concept Our intent is to cover the fundamental concepts of data mining, to dem- strate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. We have organized the material into three parts. Part I introduces concepts. Part II contains chapters on a number of different techniques often used in data mining. Part III focuses on business applications of data mining. Not all of these chapters need to be covered, and their sequence could be varied at instructor design. The book will include short vignettes of how specific concepts have been applied in real practice. A series of representative data sets will be generated to demonstrate specific methods and concepts. References to data mining software and sites such as www.kdnuggets.com will be provided. Part I: Introduction Chapter 1 gives an overview of data mining, and provides a description of the data mining process. An overview of useful business applications is provided.
Reviews
From the reviews:
"Text analysis and data mining have become increasingly important capabilities in today’s information-flooded world, and choosing the right technique makes all the difference. This book contains some advanced data mining techniques, but also includes an overview of important data mining fundamentals, specifically the CRISP-DM and SEMMA industry standards. … Summing Up: Recommended. Upper-division undergraduates and up." (H. J. Bender, CHOICE, Vol. 45 (11), August, 2008)
Authors and Affiliations
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Department of Management Science, University of Nebraska, Lincoln, USA
David L. Olson
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Department of Management, Science and Information Systems, Tulsa, USA
Dursun Delen
