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>.
| Version: | 1.3.1 |
| 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) |
| Published: | 2025-01-29 |
| DOI: | 10.32614/CRAN.package.GeneralizedUmatrix |
| Author: | Michael Thrun [aut, cre, cph], Felix Pape [ctb, ctr], Tim Schreier [ctb, ctr], Luis Winckelman [ctb, ctr], Quirin Stier [ctb, ctr], Alfred Ultsch [ths] |
| Maintainer: | Michael Thrun <m.thrun at gmx.net> |
| BugReports: | https://github.com/Mthrun/GeneralizedUmatrix/issues |
| License: | GPL-3 |
| URL: | https://www.deepbionics.org |
| NeedsCompilation: | yes |
| SystemRequirements: | GNU make, pandoc (>=1.12.3, needed for vignettes) |
| Citation: | GeneralizedUmatrix citation info |
| Materials: | README |
| CRAN checks: | GeneralizedUmatrix results |