Projection-Based Clustering through Self-Organization and Swarm Intelligence
Springer Fachmedien Wiesbaden GmbH (Verlag)
978-3-658-20539-3 (ISBN)
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.
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.
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).
| Erscheinungsdatum | 04.02.2018 |
|---|---|
| Zusatzinfo | XX, 201 p. 90 illus., 29 illus. in color. |
| Verlagsort | Wiesbaden |
| Sprache | englisch |
| Maße | 168 x 240 mm |
| Gewicht | 383 g |
| Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
| Informatik ► Theorie / Studium ► Algorithmen | |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Schlagworte | 3D Printing • Advanced Analytics • Analysis of stuctured data • cluster analysis • Data Science • data structures • dimensionality reduction • Emergence • Game Theory • high-dimensional data • Knowledge Discovery • multivariate data • open access • Self-Organization • Swarm intelligence • unsupervised machine learning • Visualization |
| ISBN-10 | 3-658-20539-3 / 3658205393 |
| ISBN-13 | 978-3-658-20539-3 / 9783658205393 |
| Zustand | Neuware |
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