doi:10.1007/978-3-658-20540-9>. This could lead to a misleading interpretation of the underlying structures [Thrun, 2018]. By means of the 3D topographic map the generalized Umatrix is able to depict errors of these two-dimensional scatter plots. The package is derived from the book of Thrun, M.C.: "Projection Based Clustering through Self-Organization and Swarm Intelligence" (2018) <doi:10.1007/978-3-658-20540-9> and the main algorithm called simplified self-organizing map for dimensionality reduction methods is published in Thrun, M.C. and Ultsch, A.: "Uncovering High-dimensional Structures of Projections from Dimensionality Reduction Methods" (2020) <doi:10.1016/j.mex.2020.101093>.">

GeneralizedUmatrixGPU: Credible Visualization for Two-Dimensional Projections of Data (original) (raw)

Projections are common dimensionality reduction methods, which represent high-dimensional data in a two-dimensional space. However, when restricting the output space to two dimensions, which results in a two dimensional scatter plot (projection) of the data, low dimensional similarities do not represent high dimensional distances coercively [Thrun, 2018] <doi:10.1007/978-3-658-20540-9>. This could lead to a misleading interpretation of the underlying structures [Thrun, 2018]. By means of the 3D topographic map the generalized Umatrix is able to depict errors of these two-dimensional scatter plots. The package is derived from the book of Thrun, M.C.: "Projection Based Clustering through Self-Organization and Swarm Intelligence" (2018) <doi:10.1007/978-3-658-20540-9> and the main algorithm called simplified self-organizing map for dimensionality reduction methods is published in Thrun, M.C. and Ultsch, A.: "Uncovering High-dimensional Structures of Projections from Dimensionality Reduction Methods" (2020) <doi:10.1016/j.mex.2020.101093>.

Version: 0.1.8
Depends: R (≥ 3.0)
Imports: Rcpp (≥ 1.0.8), RcppParallel (≥ 5.1.4), ggplot2, GeneralizedUmatrix
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
Suggests: DataVisualizations, rgl, grid, mgcv, png, reshape2, fields, ABCanalysis, plotly, deldir, methods, knitr (≥ 1.12), rmarkdown (≥ 0.9), ProjectionBasedClustering
Published: 2025-11-17
DOI: 10.32614/CRAN.package.GeneralizedUmatrixGPU
Author: Quirin Stier ORCID iD [aut, cre], Michael Thrun ORCID iD [aut, cph], The Khronos Group Inc. [cph]
Maintainer: Quirin Stier <Quirin_Stier at gmx.de>
License: GPL-3
NeedsCompilation: yes
SystemRequirements: GNU make, pandoc (>=1.12.3, needed for vignettes), OpenCL shared library (provided by an SDK such as AMD/NVIDIA)
Citation: GeneralizedUmatrixGPU citation info
CRAN checks: GeneralizedUmatrixGPU results

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