data.gauss: Gaussian mixture dataset

In fdm2id: Data Mining and R Programming for Beginners

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 = TRUE,
  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	A logical indicating whether or not a graphic should be plotted.
seed	A specified seed for random number generation.

Value

A randomly generated dataset.

See Also

data.diag, data.parabol, data.target2, data.twomoons, data.xor

Examples

data.gauss ()

fdm2id documentation built on July 9, 2023, 6:05 p.m.