Other packages > Find by keyword >

DatabionicSwarm  

Swarm Intelligence for Self-Organized Clustering
View on CRAN: Click here


Download and install DatabionicSwarm package within the R console
Install from CRAN:
install.packages("DatabionicSwarm")

Install from Github:
library("remotes")
install_github("cran/DatabionicSwarm")

Install by package version:
library("remotes")
install_version("DatabionicSwarm", "2.0.0")



Attach the package and use:
library("DatabionicSwarm")
Maintained by
Michael Thrun
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-08-20
Latest Update: 2024-06-20
Description:
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, . 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) .
How to cite:
Michael Thrun (2017). DatabionicSwarm: Swarm Intelligence for Self-Organized Clustering. R package version 2.0.0, https://cran.r-project.org/web/packages/DatabionicSwarm. Accessed 20 Sep. 2026.
Previous versions and publish date:
0.9.7 (2017-08-20 13:13), 0.9.8 (2017-09-28 19:55), 1.0.0 (2018-01-31 19:00), 1.0.1 (2018-03-07 08:51), 1.0.3 (2018-05-06 18:45), 1.1.0 (2018-07-03 10:30), 1.1.1 (2019-01-27 15:20), 1.1.2 (2019-12-11 18:30), 1.1.3 (2020-02-03 15:00), 1.1.5 (2021-01-12 20:20), 1.1.6 (2022-11-29 09:50), 1.2.0 (2023-05-30 10:50), 1.2.1 (2023-10-13 13:30), (2026-07-09 08:02)
Other packages that cited DatabionicSwarm R package
View DatabionicSwarm citation profile
Other R packages that DatabionicSwarm depends, imports, suggests or enhances
Complete documentation for DatabionicSwarm
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
RWmisc  
Miscellaneous Spatial Functions
Contains convenience functions for working with spatial data across multiple UTM zones, raster-vect ...
Download / Learn more Package Citations See dependency  
WASP  
Wavelet System Prediction
The wavelet-based variance transformation method is used for system modelling and prediction. It ref ...
Download / Learn more Package Citations See dependency  
migration.indices  
Migration Indices
Calculate various indices, like Crude Migration Rate, different Gini indices or the Coefficient of ...
Download / Learn more Package Citations See dependency  
MatchThem  
Matching and Weighting Multiply Imputed Datasets
Provides essential tools for the pre-processing techniques of matching and weighting multiply impute ...
Download / Learn more Package Citations See dependency  
relimp  
Relative Contribution of Effects in a Regression Model
Functions to facilitate inference on the relative importance of predictors in a linear or generalize ...
Download / Learn more Package Citations See dependency  

28,565

R Packages

239,283

Dependencies

75,677

Author Associations

28,566

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA