Projection-Based Clustering through Self-Organization and Swarm Intelligence

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. 

• 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
• data structures

• Marburg, Germany

  Michael Christoph Thrun

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.

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