plot.ppci_projection_solution: Visualise a Data Set Projected from Projection Pursuit

In DavidHofmeyr/PPCI: Projection Pursuit for Cluster Identification

Description

Provides a visualisation of a data set using a low dimensional projection obtained using projection pursuit based on cluster based projection indices.

Usage

## S3 method for class 'ppci_projection_solution'
plot(x, labels = NULL, pairs = NULL, PCA = NULL, transparency = NULL, ...)

Arguments

x	a solution arising from one of the functions mcdr, mddr and ncutdr.
labels	(optional) a vector of class labels. if provided then points in different classes are plotted in different colours.
pairs	(optional) if omitted then the first two dimensions are shown. If an integer > 1 then all pairs from the first 1:pairs dimensions are shown.
PCA	(optional) logical. If TRUE then an additional principal component rotation is applied. This can make more clusters visible within a low dimensional projection.
transparency	(optional) if ommitted then points in scatterplots are shown as solid. If set to a value in (0, 1) then points are shown with transparency. Lower values correspond with a greater degree of transparency.
...	additional graphical parameters. Currently none implemented.

Value

None

See Also

mcdr, mddr, ncutdr

DavidHofmeyr/PPCI documentation built on March 9, 2020, 5:05 p.m.