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)
|Author||Michael Thrun [aut, cre, cph], Alfred Ultsch [ths]|
|Date of publication||2018-01-31 18:13:07 UTC|
|Maintainer||Michael Thrun <[email protected]>|
|Package repository||View on CRAN|
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