plot.ppci_hyperplane_solution

a solution arising from one of the functions mch, mdh and ncuth.

(optional) a vector of class labels. if provided then points in different classes are plotted in different colours.

labels

(optional) if ommitted then points in the scatterplot 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.

transparency

additional graphical parameters. Currently none implemented.

Provides a visualisation of the partition induced by a hyperplane separator generated by one of mch, mdh and ncuth.

internal

Implements recently developed projection
pursuit algorithms for finding optimal linear cluster
separators. The clustering algorithms use optimal
hyperplane separators based on minimum density, Pavlidis et. al (2016) <http://jmlr.org/papers/volume17/15-307/15-307.pdf>;
minimum normalised cut, Hofmeyr (2017) <doi:10.1109/TPAMI.2016.2609929>;
and maximum variance ratio clusterability, Hofmeyr and Pavlidis (2015) <doi:10.1109/SSCI.2015.116>.

plot.ppci_hyperplane_solution: Visualise a Hyperplane Separator for Clustering

Description

Usage

Arguments

Value

See Also