data.gauss: Gaussian mixture dataset
In fdm2id: Data Mining and R Programming for Beginners

data.gauss

R Documentation

Gaussian mixture dataset

Description

Generate a random multidimentional gaussian mixture.

Usage

data.gauss(
  n = 1000,
  k = 2,
  prob = rep(1/k, k),
  mu = cbind(rep(0, k), seq(from = 0, by = 3, length.out = k)),
  cov = rep(list(matrix(c(6, 0.9, 0.9, 0.3), ncol = 2, nrow = 2)), k),
  levels = NULL,
  graph = FALSE,
  seed = NULL
)

Arguments

`n`	Number of observations.
`k`	The number of classes.
`prob`	The a priori probability of each class.
`mu`	The means of the gaussian distributions.
`cov`	The covariance of the gaussian distributions.
`levels`	Name of each class.
`graph`	Whether the generated dataset is plotted. `FALSE` by default, as everywhere else in the package: a generator has to be callable in a loop or a report without piling up graphics devices.
`seed`	A specified seed for random number generation.