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The created data are d-dimensional spherical Gaussians with standard deviation sd and means at the corners of a d-dimensional hypercube. The number of classes is \(2^d\).
d
sd
mlbench.hypercube(n=800, d=3, sides=rep(1,d), sd=0.1) hypercube(d)
number of patterns to create
dimensionality of hypercube, default is 3
lengths of the sides of the hypercube, default is to create a unit hypercube
standard deviation
Returns an object of class "mlbench.hypercube" with components
"mlbench.hypercube"
input values
factor of length n with target classes
n
# NOT RUN { p <- mlbench.hypercube() plot(p) library("lattice") cloud(x.3~x.1+x.2, groups=classes, data=as.data.frame(p)) # }
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