Projection-Based Clustering through Self-Organization and Swarm Intelligence
Combining Cluster Analysis with the Visualization of High-Dimensional Data
(Sprache: Englisch)
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...
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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.
Inhaltsverzeichnis zu „Projection-Based Clustering through Self-Organization and Swarm Intelligence “
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).Autoren-Porträt von 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.
Bibliographische Angaben
- Autor: Michael Christoph Thrun
- 2018, 1st ed. 2018, XX, 201 Seiten, 29 farbige Abbildungen, Maße: 16,8 x 24 cm, Kartoniert (TB), Englisch
- Verlag: Springer, Berlin
- ISBN-10: 3658205393
- ISBN-13: 9783658205393
- Erscheinungsdatum: 22.01.2018
Sprache:
Englisch
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