Gaussian mixture dataset
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 )
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. |
A randomly generated dataset.
data.gauss ()
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