Package: DatabionicSwarm 1.3.0
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>.
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DatabionicSwarm_1.3.0.tar.gz
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DatabionicSwarm.pdf |DatabionicSwarm.html✨
DatabionicSwarm/json (API)
# Install 'DatabionicSwarm' in R: |
install.packages('DatabionicSwarm', repos = c('https://mthrun.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mthrun/databionicswarm/issues
- DefaultColorSequence - Default color sequence for plots
- Hepta - Hepta is part of the Fundamental Clustering Problem Suit (FCPS) [Thrun/Ultsch, 2020].
- Lsun3D - Lsun3D is part of the Fundamental Clustering Problem Suit (FCPS) [Thrun/Ultsch, 2020].
Last updated 10 months agofrom:442e97529e. Checks:OK: 1 ERROR: 8. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Aug 09 2024 |
R-4.5-win-x86_64 | ERROR | Aug 09 2024 |
R-4.5-linux-x86_64 | ERROR | Aug 09 2024 |
R-4.4-win-x86_64 | ERROR | Aug 09 2024 |
R-4.4-mac-x86_64 | ERROR | Aug 09 2024 |
R-4.4-mac-aarch64 | ERROR | Aug 09 2024 |
R-4.3-win-x86_64 | ERROR | Aug 09 2024 |
R-4.3-mac-x86_64 | ERROR | Aug 09 2024 |
R-4.3-mac-aarch64 | ERROR | Aug 09 2024 |
Exports:DBSclusteringDelaunay4PointsDijkstraSSSPGeneratePswarmVisualizationProjectedPoints2GridPswarmRelativeDifferencesESOM4BMUssetGridSizeShortestGraphPathsCUniquePoints
Dependencies:clicolorspacedeldirfansifarverGeneralizedUmatrixggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppArmadilloRcppParallelrlangscalestibbleutf8vctrsviridisLitewithr