tree_plot

a clustering solution arising from one of the functions mcdc, mddc and ncutdc.

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

labels

(optional) logical. if TRUE then numbers are added to the plot to indicate the order in which nodes were added to the model. if omitted then node.numbers = TRUE.

node.numbers

(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.

transparency

Provides a visualisation of a hierarchical clustering model via two-dimensional projections of the data assigned to each node.

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>.

tree_plot: Visualise a Hierarchical Clustering Model

Description

Usage

Arguments