The inputs of the twonorm problem are points from two Gaussian
distributions with unit covariance matrix. Class 1 is multivariate
normal with mean \((a,a,\ldots,a)\) and class 2 with mean
\((-a,-a,\ldots,-a)\), \(a=2/d^{0.5}\).
Usage
mlbench.twonorm(n, d=20)
Value
Returns an object of class "mlbench.twonorm" with components
x
input values
classes
factor vector of length n with target classes
Arguments
n
number of patterns to create
d
dimension of the twonorm problem
References
Breiman, L. (1996). Bias, variance, and arcing classifiers.
Tech. Rep. 460, Statistics Department, University of California,
Berkeley, CA, USA.