mlbench (version 2.1-3)

mlbench.threenorm: Threenorm Benchmark Problem

Description

The inputs of the threenorm problem are points from two Gaussian distributions with unit covariance matrix. Class 1 is drawn with equal probability from a unit multivariate normal with mean \((a,a,\ldots,a)\) and from a unit multivariate normal with mean \((-a,-a,\ldots,-a)\). Class 2 is drawn from a multivariate normal with mean at \((a,-a,a, \ldots,-a)\), \(a=2/d^{0.5}\).

Usage

mlbench.threenorm(n, d=20)

Arguments

n

number of patterns to create

d

dimension of the threenorm problem

Value

Returns an object of class "mlbench.threenorm" with components

x

input values

classes

factor vector of length n with target classes

References

Breiman, L. (1996). Bias, variance, and arcing classifiers. Tech. Rep. 460, Statistics Department, University of California, Berkeley, CA, USA.

Examples

# NOT RUN {
p<-mlbench.threenorm(1000, d=2)
plot(p)
# }