Credible Visualization for Two-Dimensional Projections of Data R package GeneralizedUmatrix version 1.3.1 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 <DOI: 10.1016/j.mex.2020.101093>. Software Depends: R (>= 3.0) Imports: Rcpp (>= 1.0.8), RcppParallel (>= 5.1.4), ggplot2 LinkingTo: Rcpp, RcppArmadillo, RcppParallel Suggests: DataVisualizations, rgl, grid, mgcv, png, reshape2, fields, ABCanalysis, plotly, deldir, methods, knitr (>= 1.12), rmarkdown (>= 0.9) Michael Thrun <m.thrun@gmx.net> Comprehensive R Archive Network (CRAN) Michael Thrun [aut, cre, cph] (ORCID: <https://orcid.org/0000-0001-9542-5543>), Felix Pape [ctb, ctr], Tim Schreier [ctb, ctr], Luis Winckelman [ctb, ctr], Quirin Stier [ctb, ctr] (ORCID: <https://orcid.org/0000-0002-7896-4737>), Alfred Ultsch [ths] GPL-3 2025-01-29 application/tgz https://CRAN.R-project.org/package=GeneralizedUmatrix doi:10.32614/CRAN.package.GeneralizedUmatrix