interactiveClustering {ProjectionBasedClustering} | R Documentation |
GUI for interactive cluster analysis
Description
This tool is an interactive shiny tool that visualizes a given generalized Umatrix and allows the user to select areas and mark them as clusters to improve a projection based clustering.
Arguments
Umatrix |
[1:Lines,1:Columns] Matrix of Umatrix Heights |
Bestmaches |
[1:n,1:2] Array with positions of Bestmatches |
Cls |
[1:n] Classification of the Bestmatches |
Details
Clicking on "Quit" returns the Cls vector to the workspace.
Value
List of
EnlargedUmatrix |
[1:Lines,1:Columns] Matrix of Umatrix Heights taken four times and arranged in a square 2x2. |
EnlargedBestmaches |
[1:n,1:2] Array with positions of Bestmatches according to the enlarged umatrix. |
EnlargedCls |
[1:n] Classification of the Bestmatches according to the enlarged umatrix. |
Umatrix |
[1:Lines,1:Columns] Matrix of Umatrix Heights |
Bestmaches |
[1:n,1:2] Array with positions of Bestmatches |
Cls |
[1:n] Classification of the Bestmatches |
TopView_TopographicMap |
Plot of a topographic map. |
Note
If you want to verifiy your clustering result externally, you can use Heatmap
or SilhouettePlot
of the CRAN package DataVisualizations
.
Author(s)
Florian Lerch, Michael Thrun
References
[Thrun/Ultsch, 2017] Thrun, M.C., Ultsch, A.: Projection based Clustering, Conf. Int. Federation of Classification Societies (IFCS),DOI:10.13140/RG.2.2.13124.53124, Tokyo, 2017.
[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, doi:10.1007/978-3-658-20540-9, 2018.
Examples
data('Hepta')
#2d projection
# Visualizuation of GeneralizedUmatrix
projectionpoints=NeRV(Hepta$Data)
#Computation of Generalized Umatrix
library(GeneralizedUmatrix)
visualization=GeneralizedUmatrix(Data = Hepta$Data,projectionpoints)
## Semi-Automatic Clustering done interactivly in a shiny gui
## Not run:
Cls = interactiveClustering(visualization$Umatrix, visualization$Bestmatches)
##Plotting
plotTopographicMap(visualization$Umatrix,visualization$Bestmatches,Cls)
## End(Not run)