2020 •
DatabionicSwarm for Projection-based Classification of Chemical Groups for Provenance Analysis of Archaeological Materials
Authors:
Thrun, Michael C.
Abstract:
Package that will be attached to Projection-based Classification of Chemical Groups for Provenance Analysis of Archaeological Materials. The swarm system called Databionic swarm (DBS) was published in Thrun, M.C., Ultsch A.: "Swarm Intelligence for Self-Organized Clustering" (2020), Artificial Intelligence, . DBS is able to adapt itself to structures of high-dimensional data such as natural clusters characterized by distance and/or density based structures in the data space. The first module is the parameter-free projection method called Pswarm (...)
Package that will be attached to Projection-based Classification of Chemical Groups for Provenance Analysis of Archaeological Materials. The swarm system called Databionic swarm (DBS) was published in Thrun, M.C., Ultsch A.: "Swarm Intelligence for Self-Organized Clustering" (2020), Artificial Intelligence, . DBS is able to adapt itself to structures of high-dimensional data such as natural clusters characterized by distance and/or density based structures in the data space. The first module is the parameter-free projection method called Pswarm (Pswarm()), which exploits the concepts of self-organization and emergence, game theory, swarm intelligence and symmetry considerations. The second module is the parameter-free high-dimensional data visualization technique, which generates projected points on the topographic map with hypsometric tints defined by the generalized U-matrix (GeneratePswarmVisualization()). The third module is the clustering method itself with non-critical parameters (DBSclustering()). Clustering can be verified by the visualization and vice versa. The term DBS refers to the method as a whole. It enables even a non-professional in the field of data mining to apply its algorithms for visualization and/or clustering to data sets with completely different structures drawn from diverse research fields. The comparison to common projection methods can be found in the book of Thrun, M.C.: "Projection Based Clustering through Self-Organization and Swarm Intelligence" (2018) . For details, please see the vignette in https://cran.r-project.org/web/packages/DatabionicSwarm/vignettes/DatabionicSwarm.html (Read More)
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