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]. 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 based on the book of Thrun, M.C.: "Projection Based Clustering through Self-Organization and Swarm Intelligence" (2018) <doi:10.1007/978-3-658-20540-9>.
| Version: |
1.1.9 |
| Depends: |
R (≥ 3.0) |
| Imports: |
Rcpp, ggplot2 |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
DataVisualizations, DatabionicSwarm, rgl, grid, mgcv, png, ProjectionBasedClustering, reshape2, fields, ABCanalysis, plotly, deldir, shiny, methods, knitr (≥ 1.12), rmarkdown (≥
0.9) |
| Published: |
2020-03-23 |
| Author: |
Michael Thrun 
[aut, cre, cph],
Felix Pape [ctb, ctr],
Tim Schreier [ctb, ctr],
Luis Winckelman [ctb, ctr],
Alfred Ultsch [ths] |
| Maintainer: |
Michael Thrun <m.thrun at gmx.net> |
| BugReports: |
https://github.com/Mthrun/GeneralizedUmatrix/issues |
| License: |
GPL-3 |
| URL: |
http://www.deepbionics.org |
| NeedsCompilation: |
yes |
| SystemRequirements: |
C++11 |
| Citation: |
GeneralizedUmatrix citation info |
| CRAN checks: |
GeneralizedUmatrix results |