gen_nonlinear

This function generates a dataset representing a nonlinear hyperbola structure.

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

gen_nonlinear function

<dl><dt>n</dt>
<dd>A numeric value (default: 500) representing the sample size.</dd>
<dt>hc</dt>
<dd>A numeric value (default: 1) representing the hyperbolic component which define the steepness and vertical scaling of the hyperbola. Larger values of this make the curve more pronounced (sharper dips/rises near 0), while smaller values make it flatter.</dd>
<dt>non_fac</dt>
<dd>A numeric value (default: 1) representing the nonlinear factor which describes the strength of this sinusoidal effect. When this is 0, the curve is purely hyperbolic; as it increases, the wave-like fluctuations become more prominent.</dd></dl>

Arguments

Generate Nonlinear Hyperbola — gen_nonlinear

<dl>

<dt>n</dt>
<dd>A numeric value (default: 500) representing the sample size.</dd>


<dt>hc</dt>
<dd>A numeric value (default: 1) representing the hyperbolic component which define the steepness and vertical scaling of the hyperbola. Larger values of this make the curve more pronounced (sharper dips/rises near 0), while smaller values make it flatter.</dd>


<dt>non_fac</dt>
<dd>A numeric value (default: 1) representing the nonlinear factor which describes the strength of this sinusoidal effect. When this is 0, the curve is purely hyperbolic; as it increases, the wave-like fluctuations become more prominent.</dd>

</dl>

gen_nonlinear: Generate Nonlinear Hyperbola

Description

Usage

Value

Arguments

Examples