DSD_Cubes: Static Cubes Data Stream Generator

In stream: Infrastructure for Data Stream Mining

Static Cubes Data Stream Generator

Description

A data stream generator that produces a data stream with static (hyper) cubes filled uniformly with data points.

Usage

DSD_Cubes(k = 2, d = 2, center, size, p, noise = 0, noise_range)

Arguments

k	Determines the number of clusters.
d	Determines the number of dimensions.
center	A matrix of means for each dimension of each cluster.
size	A k times d matrix with the cube dimensions.
p	A vector of probabilities that determines the likelihood of generated a data point from a particular cluster.
noise	Noise probability between 0 and 1. Noise is uniformly distributed within noise range (see below).
noise_range	A matrix with d rows and 2 columns. The first column contains the minimum values and the second column contains the maximum values for noise.

Value

Returns a DSD_Cubes object (subclass of DSD_R, DSD).

Author(s)

Michael Hahsler

See Also

Other DSD: DSD(), DSD_BarsAndGaussians(), DSD_Benchmark(), DSD_Gaussians(), DSD_MG(), DSD_Memory(), DSD_Mixture(), DSD_NULL(), DSD_ReadDB(), DSD_ReadStream(), DSD_Target(), DSD_UniformNoise(), DSD_mlbenchData(), DSD_mlbenchGenerator(), DSF(), animate_data(), close_stream(), get_points(), plot.DSD(), reset_stream()

Examples

# create data stream with three clusters in 3D
stream <- DSD_Cubes(k = 3, d = 3, noise = 0.05)

get_points(stream, n = 5)

plot(stream)

stream documentation built on April 4, 2025, 1:02 a.m.