DatabionicSwarm: Swarm Intelligence for Self-Organized Clustering
Algorithms implementing populations of agents that interact with one another and sense their environment may exhibit emergent behavior such as self-organization and swarm intelligence. Here, a swarm system called Databionic swarm (DBS) is introduced which was published in Thrun, M.C., Ultsch A.: "Swarm Intelligence for Self-Organized Clustering" (2020), Artificial Intelligence, <doi:10.1016/j.artint.2020.103237>. 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) <doi:10.1007/978-3-658-20540-9>.
| Version: |
2.0.0 |
| Depends: |
R (≥ 3.0) |
| Imports: |
Rcpp (≥ 1.0.8), RcppParallel (≥ 5.1.4), deldir, GeneralizedUmatrix, ABCanalysis, ggplot2 |
| LinkingTo: |
Rcpp, RcppArmadillo, RcppParallel |
| Suggests: |
DataVisualizations, knitr (≥ 1.12), rmarkdown (≥ 0.9), plotrix, geometry, sp, spdep, parallel, rgl, png, ProjectionBasedClustering, parallelDist, pracma, dendextend |
| Published: |
2024-06-20 |
| DOI: |
10.32614/CRAN.package.DatabionicSwarm |
| Author: |
Michael Thrun 
[aut, cre, cph],
Quirin Stier
[aut, rev] |
| Maintainer: |
Michael Thrun <m.thrun at gmx.net> |
| BugReports: |
https://github.com/Mthrun/DatabionicSwarm/issues |
| License: |
GPL-3 |
| URL: |
https://www.deepbionics.org/ |
| NeedsCompilation: |
yes |
| SystemRequirements: |
GNU make, pandoc (>=1.12.3, needed for vignettes) |
| Citation: |
DatabionicSwarm citation info |
| Materials: |
NEWS |
| In views: |
Cluster |
| CRAN checks: |
DatabionicSwarm results |
Documentation:
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