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Table of contents

  1. Front Matter
    Pages I-XX
  2. Michael Christoph Thrun
    Pages 1-3 Open Access
  3. Michael Christoph Thrun
    Pages 5-20 Open Access
  4. Michael Christoph Thrun
    Pages 21-31 Open Access
  5. Michael Christoph Thrun
    Pages 33-42 Open Access
  6. Michael Christoph Thrun
    Pages 43-53 Open Access
  7. Michael Christoph Thrun
    Pages 55-75 Open Access
  8. Michael Christoph Thrun
    Pages 77-89 Open Access
  9. Michael Christoph Thrun
    Pages 91-106 Open Access
  10. Michael Christoph Thrun
    Pages 107-116 Open Access
  11. Michael Christoph Thrun
    Pages 117-127 Open Access
  12. Michael Christoph Thrun
    Pages 129-136 Open Access
  13. Michael Christoph Thrun
    Pages 137-148 Open Access
  14. Michael Christoph Thrun
    Pages 149-159 Open Access
  15. Michael Christoph Thrun
    Pages 161-162 Open Access
  16. Back Matter
    Pages 163-201

About this book

Introduction

This book is published open access under a CC BY 4.0 license.

It covers aspects of unsupervised machine learning used for knowledge discovery in data science and introduces a data-driven approach to cluster analysis, the Databionic swarm(DBS). DBS consists of the 3D landscape visualization and clustering of data. The 3D landscape enables 3D printing of high-dimensional data structures.The clustering and number of clusters or an absence of cluster structure are verified by the 3D landscape at a glance. DBS is the first swarm-based technique that shows emergent properties while exploiting concepts of swarm intelligence, self-organization and the Nash equilibrium concept from game theory. It results in the elimination of a global objective function and the setting of parameters. By downloading the R package DBS can be applied to data drawn from diverse research fields and used even by non-professionals in the field of data mining. 

Contents
  • Approaches to Unsupervised Machine Learning
  • Methods of Visualization of High-Dimensional Data
  • Quality Assessments of Visualizations
  • Behavior-Based Systems in Data Science
  • Databionic Swarm (DBS)
Target Groups
Lecturers, students as well as non-professional users of data science, statistics, computer science, business mathematics, medicine, biology

The Author
Michael C. Thrun, Dipl.-Phys., successfully defended his Ph.D. in 2017 at the Philipps University of Marburg. Thrun’s advisor was the Chair of Neuroinformatics, Prof. Dr. rer. nat. Alfred G. H. Ultsch.

Keywords

Open Access Cluster Analysis Dimensionality Reduction Swarm Intelligence Visualization Unsupervised machine learning Data science Knowledge Discovery 3D printing Self-Organization Emergence Game theory Advanced Analytics High-dimensional data Multivariate data Analysis of stuctured data

Authors and affiliations

  • Michael Christoph Thrun
    • 1
  1. 1.MarburgGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-658-20540-9
  • Copyright Information The Editor(s) (if applicable) and The Author(s) 2018
  • License CC BY
  • Publisher Name Springer Vieweg, Wiesbaden
  • eBook Packages Computer Science
  • Print ISBN 978-3-658-20539-3
  • Online ISBN 978-3-658-20540-9
  • Buy this book on publisher's site