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).
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.
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()
,
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()
# 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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