plotMDS: Plot observations using multidimensional scaling and colour...

Description Usage Arguments See Also Examples

View source: R/densityClust.R

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

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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

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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)

densityClust documentation built on May 2, 2019, 6:59 a.m.