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Descriptive Data Mining

  • David L.¬†Olson

Part of the Computational Risk Management book series (Comp. Risk Mgmt)

Table of contents

  1. Front Matter
    Pages i-xi
  2. David L. Olson
    Pages 1-7
  3. David L. Olson
    Pages 9-28
  4. David L. Olson
    Pages 29-41
  5. David L. Olson
    Pages 43-59
  6. David L. Olson
    Pages 61-69
  7. David L. Olson
    Pages 71-95
  8. David L. Olson
    Pages 97-111
  9. David L. Olson
    Pages 113-114
  10. Back Matter
    Pages 115-116

About this book

Introduction

This book offers an overview of knowledge management. It starts with an introduction to the subject, placing descriptive models in the context of the overall field as well as within the more specific field of data mining analysis. Chapter 2 covers data visualization, including directions for accessing R open source software (described through Rattle). Both R and Rattle are free to students. Chapter 3 then describes market basket analysis, comparing it with more advanced models, and addresses the concept of lift. Subsequently, Chapter 4 describes smarketing RFM models and compares it with more advanced predictive models. Next, Chapter 5 describes association rules, including the APriori algorithm and provides software support from R. Chapter 6 covers cluster analysis, including software support from R (Rattle), KNIME, and WEKA, all of which are open source. Chapter 7 goes on to describe link analysis, social network metrics, and open source NodeXL software, and demonstrates link analysis application using PolyAnalyst output. Chapter 8 concludes the monograph.

Using business-related data to demonstrate models, this descriptive book explains how methods work with some citations, but without detailed references. The data sets and software selected are widely available and can easily be accessed.

Keywords

Business Analytics Data Mining Descriptive Data Mining Visualization Open Source Software Cluster Analysis Big Data

Authors and affiliations

  • David L.¬†Olson
    • 1
  1. 1.College of BusinessUniversity of NebraskaLincolnUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-981-10-3340-7
  • Copyright Information Springer Nature Singapore Pte Ltd. 2017
  • Publisher Name Springer, Singapore
  • eBook Packages Business and Management
  • Print ISBN 978-981-10-3339-1
  • Online ISBN 978-981-10-3340-7
  • Series Print ISSN 2191-1436
  • Series Online ISSN 2191-1444
  • Buy this book on publisher's site
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