ClusterPlotMDS function

Plot Clustering using Dimensionality Reduction by MDS

Plot Clustering using Dimensionality Reduction by MDS

This function uses a projection method to perform dimensionality reduction (DR) on order to visualize the data as 3D data points colored by a clustering.

ClusterPlotMDS(DataOrDistances, Cls, main = "Clustering", DistanceMethod = "euclidean", OutputDimension = 3, PointSize=1,Plotter3D="rgl",Colorsequence, ...)

Arguments

  • DataOrDistances: Either nonsymmetric [1:n,1:d] datamatrix of n cases and d features or symmetric [1:n,1:n] distance matrix
  • Cls: 1:n numerical vector of numbers defining the classification as the main output of the clustering algorithm for the n cases of data. It has k unique numbers representing the arbitrary labels of the clustering.
  • main: String, title of plot
  • DistanceMethod: Method to compute distances, default "euclidean"
  • OutputDimension: Either two or three depending on user choice
  • PointSize: Scalar defining the size of points
  • Plotter3D: In case of 3 dimensions, choose either "plotly" or "rgl",
  • Colorsequence: [1:k] character vector of colors, per default the colorsquence defined in the DataVisualizations is used
  • ...: Please see Plot3D in DataVisualizations

Details

If dataset has more than 3 dimesions, mds is performed as defined in the smacof [De Leeuw/Mair, 2011]. If smacof package is not installed, classical metric MDS (see Def. in [Thrun, 2018]) is performed. In both cases, the first OutputDimension are visualized. Points are colored by the labels (Cls).

In the special case that the dataset has not more than 3 dimensions, all dimensions are visualized and no DR is performed.

Returns

The rgl or plotly plot handler depending on Plotter3D

References

[De Leeuw/Mair, 2011] De Leeuw, J., & Mair, P.: Multidimensional scaling using majorization: SMACOF in R, Journal of statistical Software, Vol. 31(3), pp. 1-30. 2011.

[Thrun, 2018] Thrun, M. C.: Projection Based Clustering through Self-Organization and Swarm Intelligence, doctoral dissertation 2017, Springer, ISBN: 978-3-658-20539-3, Heidelberg, 2018.

Author(s)

Michael Thrun

Note

If DataVisualizations is not installed a 2D plot using native plot function is shown.

If MASS is not installed, classicial metric MDS is used, see [Thrun, 2018] for definition.

See Also

Plot3D

Examples

data(Hepta) ClusterPlotMDS(Hepta$Data,Hepta$Cls) data(Leukemia) ClusterPlotMDS(Leukemia$DistanceMatrix,Leukemia$Cls)
  • Maintainer: Michael Thrun
  • License: GPL-3
  • Last published: 2023-10-19