GeneralizedUmatrix (version 1.2.1)

GeneralizedUmatrix-package: GeneralizedUmatrix

Description

GeneralizedUmatrix

Details

For a brief introduction to GeneralizedUmatrix please see the vignette Introduction of the Generalized Umatrix Package.

For further details regarding the generalized Umatrix see [Thrun, 2018], chapter 4-5, or [Thrun/Ultsch, 2020].

If you want to verifiy your clustering result externally, you can use Heatmap or SilhouettePlot of the CRAN package DataVisualizations.

GeneralizedUmatrix

References

[Thrun/Ultsch, 2020] Thrun, M. C., & Ultsch, A.: Uncovering High-Dimensional Structures of Projections from Dimensionality Reduction Methods, MethodsX, Vol. in press, pp. 101093. doi 10.1016/j.mex.2020.101093, 2020.

[Thrun, 2018] Thrun, M. C.: Projection Based Clustering through Self-Organization and Swarm Intelligence, doctoral dissertation 2017, Springer, Heidelberg, ISBN: 978-3-658-20539-3, https://doi.org/10.1007/978-3-658-20540-9, 2018.

[Ultsch/Thrun, 2017] Ultsch, A., & Thrun, M. C.: Credible Visualizations for Planar Projections, in Cottrell, M. (Ed.), 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization (WSOM), IEEE Xplore, France, 2017.

Examples

# NOT RUN {
data("Chainlink")
Data=Chainlink$Data
Cls=Chainlink$Cls
InputDistances=as.matrix(dist(Data))
res=cmdscale(d=InputDistances, k = 2, eig = TRUE, add = FALSE, x.ret = FALSE)
ProjectedPoints=as.matrix(res$points)
#see also ProjectionBasedClustering package for other common projection methods
#see DatabionicSwarm for projection method without parameters or objective function
# ProjectedPoints=DatabionicSwarm::Pswarm(Data)$ProjectedPoints
# }
# NOT RUN {
resUmatrix=GeneralizedUmatrix(Data,ProjectedPoints)
plotTopographicMap(resUmatrix$Umatrix,resUmatrix$Bestmatches,Cls)
# }
# NOT RUN {
##Interactive Island Generation 
## from a tiled Umatrix (toroidal assumption)
# }
# NOT RUN {
	Imx = ProjectionBasedClustering::interactiveGeneralizedUmatrixIsland(resUmatrix$Umatrix,
	resUmatrix$Bestmatches)
	plotTopographicMap(resUmatrix$Umatrix,

	resUmatrix$Bestmatches, Imx = Imx)
# }
# NOT RUN {
#External Verification
# }
# NOT RUN {
 DataVisualizations::Heatmap(Data,Cls)
 #if spherical cluster strcuture
 DataVisualizations::SilhouettePlot(Data,Cls)
# }
# NOT RUN {
# }