ExtendToroidalUmatrix

[1:Lines,1:Columns] Matrix of Umatrix Heights

Umatrix

[1:n, 1:2] Matrix with positions of Bestmatches for n datapoints, first columns is the position in <code>Lines</code> and second column in <code>Columns</code>

Bestmatches

number of lines and columns the umatrix should be extended with

ExtendBorders

Extends Umatrix by toroidal continuation of the given Umatrix defined by <code>ExtendBorders</code> in all four directions.

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>.

ExtendToroidalUmatrix: Extend Toroidal Umatrix

Description

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Examples