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

Description Usage Arguments Value

View source: R/twonormLinearData.R

Description

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

Usage

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  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.