November 2017
Beginner to intermediate
366 pages
7h 59m
English
As a simulator DSD can simulate static streams as well as streams with drift. In cases where we are developing algorithms to work on streaming data, we can use this simulator feature effectively.
Let us see how DSD can be leveraged as a data simulator:
> library(stream, quietly = TRUE)> set.seed(100)> gaussian.stream <- DSD_Gaussians(k = 3, d = 3, noise = .01)> gaussian.streamMixture of GaussiansClass: DSD_Gaussians, DSD_R, DSD_data.frame, DSD With 3 clusters in 3 dimensions > > data <- get_points(gaussian.stream, n = 100, class = TRUE)> head(data) X1 X2 X3 class1 0.3431437 0.4621701 0.4151013 22 0.6684551 0.4715456 0.4162625 33 0.2367551 0.3512569 0.7573724 14 0.4465450 0.5563404 0.4582585 25 0.3563359 0.5492573 ...
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