twonormLinearData: Generate a Binary Classification Problem with Two Gaussian...

In locClassData: Collection of Artificial Classification Problems

Description

Generate a binary classification problem with two Gaussian distributions with different means and equal covariance matrices.

Usage

  twonormLinearData(n, prior = rep(0.5, 2), mu1 = c(1, 0),
    mu2 = c(0, -1), sigma = diag(2))

  twonormLinearLabels(data, prior = rep(0.5, 2),
    mu1 = c(1, 0), mu2 = c(0, -1), sigma = diag(2))

  twonormLinearPosterior(data, prior = rep(0.5, 2),
    mu1 = c(1, 0), mu2 = c(0, -1), sigma = diag(2))

  twonormLinearBayesClass(data, prior = rep(0.5, 2),
    mu1 = c(1, 0), mu2 = c(0, -1), sigma = diag(2))

Arguments

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.
sigma	Covariance matrix for classes 1 and 2.
data	A data.frame.

Value

twonormLinearData returns an object of class "locClass", a list with components:

x	(A matrix.) The explanatory variables.
y	(A factor.) The class labels.

twonormLinearLabels returns a factor of class labels.

twonormLinearPosterior returns a matrix of posterior probabilities.

twonormLinearBayesClass returns a factor of Bayes predictions.

locClassData documentation built on May 2, 2019, 5:26 p.m.