Projection-Based Clustering through Self-Organization and Swarm Intelligence: Combining Cluster Analysis with the Visualization of High-Dimensional Data

by Michael Christoph Thrun

Overview

This open access book 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.

Product Details

ISBN-13:	9783658205393
Publisher:	Springer Fachmedien Wiesbaden
Publication date:	01/10/2018
Edition description:	1st ed. 2018
Pages:	201
Product dimensions:	6.61(w) x 9.45(h) x (d)

About 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.

Table of 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).