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Generate data from 2 Gaussian distributed classes
generate2ClassGaussian(n = 10000, d = 100, var = 1, expected = TRUE)
integer; Number of examples to generate
integer; dimensionality of the problem
numeric; size of the variance parameter
logical; whether the decision boundary should be the expected or perpendicular
Other RSSL datasets: generateABA(), generateCrescentMoon(), generateFourClusters(), generateParallelPlanes(), generateSlicedCookie(), generateSpirals(), generateTwoCircles()
generateABA()
generateCrescentMoon()
generateFourClusters()
generateParallelPlanes()
generateSlicedCookie()
generateSpirals()
generateTwoCircles()
data <- generate2ClassGaussian(n=1000,d=2,expected=FALSE) plot(data[,1],data[,2],col=data$Class,asp=1)
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