View source: R/distributions.R
Generate normally distributed feature samples for a binary classification problem
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | new_sample_mix(
n,
nu_0,
tau_0,
n_0,
sigma_0,
w_0,
nu_1,
tau_1,
n_1,
sigma_1,
w_1,
p_0
)
|
n |
integer: the size of the sample |
nu_0 |
numeric: the average mean of the components of the first class |
tau_0 |
matrix: covariance of components of the first class |
n_0 |
integer: class frequency of first feature in the sample |
sigma_0 |
matrix: covariance of observations in first class |
w_0 |
numeric: vector of weights for components of the first class |
nu_1 |
numeric: the average mean of the components of the second class |
tau_1 |
matrix: covariance of components of the second class |
n_1 |
integer: class frequency of second feature in the sample |
sigma_1 |
matrix: covariance of observations in second class |
w_1 |
numeric: vector of weights for components of the second feature |
p_0 |
double: the prior probability of class 0 |
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