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A data stream generator that produces a data stream with static (hyper) cubes filled uniformly with data points.
DSD_Cubes(k = 2, d = 2, center, size, p, noise = 0, noise_range)
Returns a DSD_Cubes object (subclass of DSD_R, DSD).
DSD_Cubes
Determines the number of clusters.
Determines the number of dimensions.
A matrix of means for each dimension of each cluster.
A k times d matrix with the cube dimensions.
k
d
A vector of probabilities that determines the likelihood of generated a data point from a particular cluster.
Noise probability between 0 and 1. Noise is uniformly distributed within noise range (see below).
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.
Michael Hahsler
Other 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(), DSD(), DSF(), animate_data(), close_stream(), get_points(), plot.DSD(), reset_stream()
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()
DSD()
DSF()
animate_data()
close_stream()
get_points()
plot.DSD()
reset_stream()
# 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)
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