GeneralizedUmatrix: Credible Visualization for Two-Dimensional Projections of Data

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: 1.0.0
Depends: R (≥ 3.0)
Imports: Rcpp, ggplot2
LinkingTo: Rcpp, RcppArmadillo
Suggests: DataVisualizations, DatabionicSwarm, matrixStats, rgl, grid, mgcv, png, ProjectionBasedClustering, reshape2, fields
Published: 2018-01-31
Author: Michael Thrun [aut, cre, cph], Alfred Ultsch [ths]
Maintainer: Michael Thrun <m.thrun at>
License: GPL-3
NeedsCompilation: yes
SystemRequirements: C++11
CRAN checks: GeneralizedUmatrix results


Reference manual: GeneralizedUmatrix.pdf
Package source: GeneralizedUmatrix_1.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: GeneralizedUmatrix_1.0.0.tgz
OS X Mavericks binaries: r-oldrel: GeneralizedUmatrix_0.9.5.tgz
Old sources: GeneralizedUmatrix archive

Reverse dependencies:

Reverse imports: DatabionicSwarm, ProjectionBasedClustering


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