mlbench.threenorm: Threenorm Benchmark Problem

In mlbench: Machine Learning Benchmark Problems

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

p<-mlbench.threenorm(1000, d=2)
plot(p)

mlbench documentation built on May 31, 2023, 6:18 p.m.