make_shape_para

This function generates synthetic high-dimensional data consisting of
\(k\) clusters of a specified shape (e.g., crescents), arranged in
parallel along alternating dimensions. The first cluster is shifted
along the first dimension, the second along the third dimension,
the third along the first dimension again, and so on.

A collection of functions to generate a large variety of
structures in high dimensions. These data structures are useful for
testing, validating, and improving algorithms used in dimensionality
reduction, clustering, machine learning, and visualization.

Jayani P. G. Lakshika

cardinalR

Collection of Data Structures

Jayani P. Gamage

Dianne Cook

Paul Harrison

Michael Lydeamore

Thiyanga S. Talagala

make_shape_para function

<dl><dt>n</dt>
<dd>A numeric vector of length \(k\), specifying the number of
observations in each cluster. All values must be positive.</dd>
<dt>k</dt>
<dd>Integer. Number of clusters to generate. Must be greater than 1.</dd>
<dt>shift</dt>
<dd>Numeric. The distance between cluster centers along the
alternating dimensions (default is `0.4`).</dd>
<dt>shape</dt>
<dd>Character string. Shape of the clusters to generate (e.g.,
`"crescent"`, `"gridcube"`, etc.). Must be a single value.</dd></dl>

Arguments

Generate Parallel Multi-Shape Clusters — make_shape_para

<dl>

<dt>n</dt>
<dd>A numeric vector of length \(k\), specifying the number of
observations in each cluster. All values must be positive.</dd>


<dt>k</dt>
<dd>Integer. Number of clusters to generate. Must be greater than 1.</dd>


<dt>shift</dt>
<dd>Numeric. The distance between cluster centers along the
alternating dimensions (default is `0.4`).</dd>


<dt>shape</dt>
<dd>Character string. Shape of the clusters to generate (e.g.,
`"crescent"`, `"gridcube"`, etc.). Must be a single value.</dd>

</dl>

make_shape_para: Generate Parallel Multi-Shape Clusters

Description

Usage

Value

Arguments

Examples