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. 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 package is based on the book of Thrun, M.C.: "Projection Based Clustering through Self-Organization and Swarm Intelligence" (2018) . A comparison to 26 common clustering algorithms on 15 datasets is presented on the website.


Version 1.1.1 (2018-07-10 GitHub) o bugfix: RelativeDifference now stops if non finite values in either x and y expaining the error

Version 1.1.0 (2018-06-26 CRAN) o Delaunay Classification Error (DCE) added. DCE evaluates projection methods unbiased.

Version 1.0.7 (GitHub)
o ClusteringAccuracy added. Given a prior Classification this function evaluates a clustering algorithm unbiased.
o Now on GitHub.

Version 1.0.6 (Local) o Bugfix: error: Cube::operator(): index out of bounds

Version 1.0.5 (Local) o RelativeDifference added which calculates the difference of a positive x and y value in the range [-2,2].

Version 1.0.4 (Local) o Minor bugfixes o Vignette added

Version 1.0.3 (2018-05-06 CRAN) o Added distance methods of ParallelCpp package

Reference manual

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1.1.1 by Michael Thrun, 3 months ago


Report a bug at https://github.com/Mthrun/DatabionicSwarm/issues

Browse source code at https://github.com/cran/DatabionicSwarm

Authors: Michael Thrun [aut, cre, cph]

Documentation:   PDF Manual  

GPL-3 license

Imports Rcpp, deldir, GeneralizedUmatrix

Suggests DataVisualizations, knitr, rmarkdown, plotrix, geometry, sp, spdep, AdaptGauss, ABCanalysis, parallel, matrixStats, rgl, png, ProjectionBasedClustering, parallelDist, pracma

Linking to Rcpp, RcppArmadillo

System requirements: C++11

Suggested by DataVisualizations, GeneralizedUmatrix.

See at CRAN