Description
Credible Visualization for Two-Dimensional Projections of Data.
Description
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>.
README.md
GeneralizedUmatrix
Installation
Installation using CRAN
Install automatically with all dependencies via
install.packages("GeneralizedUmatrix",dependencies = T)
Installation using Github
Please note, that dependecies have to be installed manually.
remotes::install_github("Mthrun/GeneralizedUmatrix")
Installation using R Studio
Please note, that dependecies have to be installed manually.
Tools -> Install Packages -> Repository (CRAN) -> GeneralizedUmatrix
Tutorial Examples
The tutorial with several examples can be found on in the vignette on CRAN:
https://cran.r-project.org/web/packages/GeneralizedUmatrix/vignettes/GeneralizedUmatrix.html
Manual
The full manual for users or developers is available here: https://cran.r-project.org/web/packages/GeneralizedUmatrix/GeneralizedUmatrix.pdf.