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

Description

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. Front Matter ....Pages I-XX Introduction (Michael Christoph Thrun)....Pages 1-3 Fundamentals (Michael Christoph Thrun)....Pages 5-20 Approaches to Cluster Analysis (Michael Christoph Thrun)....Pages 21-31 Methods of Projection (Michael Christoph Thrun)....Pages 33-42 Visualizing the Output Space (Michael Christoph Thrun)....Pages 43-53 Quality Assessments of Visualizations (Michael Christoph Thrun)....Pages 55-75 Behavior-based Systems in Data Science (Michael Christoph Thrun)....Pages 77-89 Databionic Swarm (DBS) (Michael Christoph Thrun)....Pages 91-106 Experimental Methodology (Michael Christoph Thrun)....Pages 107-116 Results on Pre-classified Data Sets (Michael Christoph Thrun)....Pages 117-127 DBS on Natural Data Sets (Michael Christoph Thrun)....Pages 129-136 Knowledge Discovery with DBS (Michael Christoph Thrun)....Pages 137-148 Discussion (Michael Christoph Thrun)....Pages 149-159 Conclusion (Michael Christoph Thrun)....Pages 161-162 Back Matter ....Pages 163-201