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Generate a random multidimentional gaussian mixture.
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 )
A randomly generated dataset.
Number of observations.
The number of classes.
The a priori probability of each class.
The means of the gaussian distributions.
The covariance of the gaussian distributions.
Name of each class.
A logical indicating whether or not a graphic should be plotted.
A specified seed for random number generation.
data.diag, data.parabol, data.target2, data.twomoons, data.xor
data.diag
data.parabol
data.target2
data.twomoons
data.xor
data.gauss ()
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