mlbench.threenorm

0th

Percentile

Threenorm Benchmark Problem

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 $(a,-a,a, \ldots,-a)$, $a=2/d^{-0.5}$.

Keywords
datagen
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
  • xinput values
  • classesfactor 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.

Aliases
  • mlbench.threenorm
Examples
p<-mlbench.threenorm(1000, d=2)
plot(p)
Documentation reproduced from package mlbench, version 0.5-1, License: Free for non-commercial purposes. See the file README and the help pages of the data sets for details.

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