DatabionicSwarm (0.9.7)

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.

Maintainer: Michael Thrun
Author(s): Michael Thrun

License: GPL-3

Uses: deldir, GeneralizedUmatrix, Rcpp, geometry, plotrix, rgl, sp, spdep, matrixStats, png, ABCanalysis, AdaptGauss, ProjectionBasedClustering
Reverse suggests: DataVisualizations, GeneralizedUmatrix

Released over 2 years ago.