Projections are common dimensionality reduction methods, which represent highdimensional data in a twodimensional 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: 10.1007/9783658205409>. 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 twodimensional scatter plots. The package is derived from the book of Thrun, M.C.: "Projection Based Clustering through SelfOrganization and Swarm Intelligence" (2018) <DOI:10.1007/9783658205409> and the main algorithm called simplified selforganizing map for dimensionality reduction methods is published in <DOI: 10.1016/j.mex.2020.101093>.
Package details 


Author  Michael Thrun [aut, cre, cph] (<https://orcid.org/0000000195425543>), Felix Pape [ctb, ctr], Tim Schreier [ctb, ctr], Luis Winckelman [ctb, ctr], Alfred Ultsch [ths] 
Maintainer  Michael Thrun <m.thrun@gmx.net> 
License  GPL3 
Version  1.2.1 
URL  http://www.deepbionics.org 
Package repository  View on CRAN 
Installation 
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