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.
