plotMDS {densityClust}

Plot observations using multidimensional scaling and colour by cluster

Description

This function produces an MDS scatterplot based on the distance matrix of the densityCluster object (if there is only the coordinates information, a distance matrix will be calculate first), and, if clusters are defined, colours each observation according to cluster affiliation. Observations belonging to a cluster core is plotted with filled circles and observations belonging to the halo with hollow circles. This plotting is not suitable for running large datasets (for example datasets with > 1000 samples). Users are suggested to use other methods, for example tSNE, etc. to visualize their clustering results too.

Usage

plotMDS(x, ...)

Arguments

x

A densityCluster object as produced by densityClust()

...

Additional parameters. Currently ignored

See Also

densityClust() for creating densityCluster objects, and plotTSNE() for an alternative plotting approach.

Examples

irisDist <- dist(iris[,1:4])
irisClust <- densityClust(irisDist, gaussian=TRUE)
plot(irisClust) # Inspect clustering attributes to define thresholds

irisClust <- findClusters(irisClust, rho=2, delta=2)
plotMDS(irisClust)
split(iris[,5], irisClust$clusters)