plot3D

[1:n,1:d] matrix with d=3, if d&gt;3 only the first 3 dimensions are taken

Data

[1:n] numeric vector of the classification of data

further arguments to be processed by <code>rgl::plot3d</code>

&#8230;

A wrapper for Data with systematic clustering colors for a x,y,z plot combined with a classification

plot3d

plot3

zplot

A collection of various visualizations methods is provided. With regards to high-dimensional data the heat map and silhouette plot for grouped data,visualizations of the distribution of distances, the scatter-density plot for two variables,the Shepard density plot as well as the Bland-Altman plot are presented here. For a classification of countries, a map of the world or Germany can be visualized. 'DataVisualizations' makes it possible to inspect the distribution of each feature of a dataset visually through the combination of four methods.More detailed explanations can be found in the book of Thrun, M.C.:"Projection-Based Clustering through Self-Organization and Swarm Intelligence" (2018) <DOI:10.1007/978-3-658-20540-9>. Furthermore, for categorical features the ABC analysis improved Pie charts, slope charts and fan plots are usable. Additionally, for measurements across a geographic area an easy to use function for a Choropleth map is presented here.

plot3D: 3D plot of points

Description

Usage

Arguments

Details

References