generate2ClassGaussian: Generate data from 2 Gaussian distributed classes

In RSSL: Implementations of Semi-Supervised Learning Approaches for Classification

Generate data from 2 Gaussian distributed classes

Description

Generate data from 2 Gaussian distributed classes

Usage

generate2ClassGaussian(n = 10000, d = 100, var = 1, expected = TRUE)

Arguments

n	integer; Number of examples to generate
d	integer; dimensionality of the problem
var	numeric; size of the variance parameter
expected	logical; whether the decision boundary should be the expected or perpendicular

See Also

Other RSSL datasets: generateABA(), generateCrescentMoon(), generateFourClusters(), generateParallelPlanes(), generateSlicedCookie(), generateSpirals(), generateTwoCircles()

Examples

data <- generate2ClassGaussian(n=1000,d=2,expected=FALSE)
plot(data[,1],data[,2],col=data$Class,asp=1)

RSSL documentation built on May 29, 2024, 2:38 a.m.