Description Usage Arguments Value
View source: R/twonormQuadraticData.R
Generate a binary classification problem with two Gaussian distributions with different means and covariance matrices.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | twonormQuadraticData(n, prior = rep(0.5, 2),
mu1 = c(1, 0), mu2 = c(0, -1), sigma1 = diag(2),
sigma2 = matrix(c(1, 0.5, 0.5, 1), 2))
twonormQuadraticLabels(data, prior = rep(0.5, 2),
mu1 = c(1, 0), mu2 = c(0, -1), sigma1 = diag(2),
sigma2 = matrix(c(1, 0.5, 0.5, 1), 2))
twonormQuadraticPosterior(data, prior = rep(0.5, 2),
mu1 = c(1, 0), mu2 = c(0, -1), sigma1 = diag(2),
sigma2 = matrix(c(1, 0.5, 0.5, 1), 2))
twonormQuadraticBayesClass(data, prior = rep(0.5, 2),
mu1 = c(1, 0), mu2 = c(0, -1), sigma1 = diag(2),
sigma2 = matrix(c(1, 0.5, 0.5, 1), 2))
|
n |
Number of observations. |
prior |
Vector of class prior probabilities. |
mu1 |
Class center of first class, a vector. |
mu2 |
Class center of second class, a vector. |
sigma1 |
Covariance matrix for class 1. |
sigma2 |
Covariance matrix for class 2. |
data |
A |
twonormQuadraticData
returns an object of class
"locClass"
, a list with components:
x |
(A matrix.) The explanatory variables. |
y |
(A factor.) The class labels. |
twonormQuadraticLabels
returns a factor of class
labels.
twonormQuadraticPosterior
returns a matrix of
posterior probabilities.
twonormQuadraticBayesClass
returns a factor of
Bayes predictions.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.