GeneralizedUmatrix

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.

Last 30 days

This package has been downloaded 466 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 17 times.

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Last 365 days

This package has been downloaded 6,669 times in the last 365 days. A solid achievement! Enough downloads to get noticed at department meetings. The day with the most downloads was Feb 12, 2025 with 92 downloads.

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