DatabionicSwarm: Swarm Intelligence for Self-Organized Clustering

Algorithms implementing populations of agents which 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 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 Pswarm, which exploits the concepts of self-organization and emergence, game theory, swarm intelligence and symmetry considerations. The second module is a parameter-free high-dimensional data visualization technique, which generates projected points on a topographic map with hypsometric colors based on the generalized U-matrix. The third module is the clustering method itself with non-critical parameters. The clustering can be verified by the visualization and vice versa. The term DBS refers to the method as a whole. DBS 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.

Version: 0.9.8
Depends: R (≥ 3.0)
Imports: Rcpp, deldir, GeneralizedUmatrix
LinkingTo: Rcpp, RcppArmadillo
Suggests: plotrix, geometry, sp, spdep, AdaptGauss, ABCanalysis, parallel, matrixStats, rgl, png, ProjectionBasedClustering
Published: 2017-09-28
Author: Michael Thrun
Maintainer: Michael Thrun <m.thrun at>
License: GPL-3
NeedsCompilation: yes
SystemRequirements: C++11
CRAN checks: DatabionicSwarm results


Reference manual: DatabionicSwarm.pdf
Package source: DatabionicSwarm_0.9.8.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: DatabionicSwarm_0.9.8.tgz
OS X Mavericks binaries: r-oldrel: DatabionicSwarm_0.9.8.tgz
Old sources: DatabionicSwarm archive


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