# mlbench.threenorm

From mlbench v0.5-1
by Friedrich Leisch

##### 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 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)
```

*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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