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ProjectionBasedClustering: Projection Based Clustering

A clustering approach applicable to every projection method is proposed here. The two-dimensional scatter plot of any projection method can construct a topographic map which displays unapparent data structures by using distance and density information of the data. The generalized U*-matrix renders this visualization in the form of a topographic map, which can be used to automatically define the clusters of high-dimensional data. The whole system is based on Thrun and Ultsch, "Using Projection based Clustering to Find Distance and Density based Clusters in High-Dimensional Data" <doi:10.1007/s00357-020-09373-2>. Selecting the correct projection method will result in a visualization in which mountains surround each cluster. The number of clusters can be determined by counting valleys on the topographic map. Most projection methods are wrappers for already available methods in R. By contrast, the neighbor retrieval visualizer (NeRV) is based on C++ source code of the 'dredviz' software package, and the Curvilinear Component Analysis (CCA) is translated from 'MATLAB' ('SOM Toolbox' 2.0) to R.

Version: 1.2.2
Depends: R (≥ 3.0)
Imports: Rcpp, ggplot2, stats, graphics, vegan, deldir, geometry, GeneralizedUmatrix, shiny, shinyjs, shinythemes, plotly, grDevices
LinkingTo: Rcpp
Suggests: DataVisualizations, fastICA, tsne, FastKNN, MASS, pcaPP, spdep, pracma, grid, mgcv, fields, png, reshape2, Rtsne, methods, dendextend, umap, uwot, DatabionicSwarm, parallelDist, parallel
Published: 2024-06-14
DOI: 10.32614/CRAN.package.ProjectionBasedClustering
Author: Michael Thrun [aut, cre, cph], Quirin Stier ORCID iD [ctb, rev], Brinkmann Luca [ctb], Florian Lerch [aut], Felix Pape [aut], Tim Schreier [aut], Luis Winckelmann [aut], Kristian Nybo [cph], Jarkko Venna [cph], van der Maaten Laurens [cph]
Maintainer: Michael Thrun <m.thrun at gmx.net>
BugReports: https://github.com/Mthrun/ProjectionBasedClustering/issues
License: GPL-3
URL: https://www.deepbionics.org
NeedsCompilation: yes
SystemRequirements: C++17
Citation: ProjectionBasedClustering citation info
Materials: README
In views: Cluster
CRAN checks: ProjectionBasedClustering results

Documentation:

Reference manual: ProjectionBasedClustering.pdf

Downloads:

Package source: ProjectionBasedClustering_1.2.2.tar.gz
Windows binaries: r-devel: ProjectionBasedClustering_1.2.2.zip, r-release: ProjectionBasedClustering_1.2.2.zip, r-oldrel: ProjectionBasedClustering_1.2.2.zip
macOS binaries: r-release (arm64): ProjectionBasedClustering_1.2.2.tgz, r-oldrel (arm64): ProjectionBasedClustering_1.2.2.tgz, r-release (x86_64): ProjectionBasedClustering_1.2.2.tgz, r-oldrel (x86_64): ProjectionBasedClustering_1.2.2.tgz
Old sources: ProjectionBasedClustering archive

Reverse dependencies:

Reverse imports: smacofx
Reverse suggests: DatabionicSwarm, DRquality, FCPS

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.