TY  - BOOK
AU  - Michael Christoph Thrun
AB  - This 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.
DO  - https://doi.org/10.1007/978-3-658-20540-9
ID  - OAPEN ID: 27229
KW  - Visualization
KW  - Knowledge Discovery
KW  - Swarm Intelligence
KW  - Unsupervised Machine Learning
KW  - Data Science
KW  - Game Theory
KW  - 3D Printing
KW  - Dimensionality Reduction
KW  - Multivariate Data
KW  - Analysis of Structured Data
KW  - Self-Organization
KW  - Emergence
KW  - Advanced Analytics
KW  - High-Dimensional Data
KW  - Cluster Analysis
L1  - https://link.springer.com/book/10.1007/978-3-658-20540-9
LA  - English
LK  - https://directory.doabooks.org/handle/20.500.12854/57169
PB  - Springer Nature
PY  - 2018
SN  - 9783658205393
SN  - 9783658205409
TI  - Projection-Based Clustering through Self-Organization and Swarm Intelligence: Combining Cluster Analysis with the Visualization of High-Dimensional Datanull
ER  - 
