Description Usage Arguments Value
Generation of a checkerboard like classification problem with 3 classes.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | xor3Data(n, prior = rep(1/3, 3), lambda = rep(1/3, 3),
mu11 = c(-4, 4), mu12 = c(0, -4), mu13 = c(4, 0),
mu21 = c(-4, 0), mu22 = c(0, 4), mu23 = c(4, -4),
mu31 = c(-4, -4), mu32 = c(0, 0), mu33 = c(4, 4),
sigma = diag(2))
xor3Labels(data, prior = rep(1/3, 3),
lambda = rep(1/3, 3), mu11 = c(-4, 4), mu12 = c(0, -4),
mu13 = c(4, 0), mu21 = c(-4, 0), mu22 = c(0, 4),
mu23 = c(4, -4), mu31 = c(-4, -4), mu32 = c(0, 0),
mu33 = c(4, 4), sigma = diag(2))
xor3Posterior(data, prior = rep(1/3, 3),
lambda = rep(1/3, 3), mu11 = c(-4, 4), mu12 = c(0, -4),
mu13 = c(4, 0), mu21 = c(-4, 0), mu22 = c(0, 4),
mu23 = c(4, -4), mu31 = c(-4, -4), mu32 = c(0, 0),
mu33 = c(4, 4), sigma = diag(2))
xor3BayesClass(data, prior = rep(1/3, 3),
lambda = rep(1/3, 3), mu11 = c(-4, 4), mu12 = c(0, -4),
mu13 = c(4, 0), mu21 = c(-4, 0), mu22 = c(0, 4),
mu23 = c(4, -4), mu31 = c(-4, -4), mu32 = c(0, 0),
mu33 = c(4, 4), sigma = diag(2))
|
n |
Number of observations. |
prior |
Vector of class prior probabilities. |
lambda |
The conditional probabilities for the mixture components given the class. Either a vector (if the same number m of mixture components is desired for each class and the conditional probabilities for each class should be equal) or a list as long as the number of classes containing one vector of probabilities for every class. The length of the k-th element is the desired number of mixture components for the k-th class. |
mu11 |
Class center of first class, a vector. |
mu12 |
Class center of first class, a vector. |
mu13 |
Class center of first class, a vector. |
mu21 |
Class center of second class, a vector. |
mu22 |
Class center of second class, a vector. |
mu23 |
Class center of second class, a vector. |
mu31 |
Class center of second class, a vector. |
mu32 |
Class center of second class, a vector. |
mu33 |
Class center of second class, a vector. |
sigma |
Covariance matrix for classes 1, 2, and 3. |
data |
A |
xor3Data
returns an object of class
"locClass"
, a list with components:
x |
(A matrix.) The explanatory variables. |
y |
(A factor.) The class labels. |
xor3Labels
returns a factor of class labels.
xor3Posterior
returns a matrix of posterior
probabilities.
xor3BayesClass
returns a factor of Bayes
predictions.
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