MathematicalEngineeringDeepLearning/R/kmeans-clustering.R at master · yoninazarathy/MathematicalEngineeringDeepLearning

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library(animation)

## set larger 'interval' if the speed is too fast

#ani.options(interval = 1)

#par(mar = c(3, 3, 1, 1.5), mgp = c(1.5, 0.5, 0))

#kmeans.ani()

# To reproduce our example you need to source the following code

source("Kmeans-animation-benoit.R")

par(mfrow=c(3,2))

ani.options('6')

pdf(file="Kmeans-algo.pdf", height=10, width=10)

#par(mar = c(5.1, 5.1, 4.1, 2.1))

par(mfrow=c(3,2))

set.seed(101)

library(mvtnorm)

x = rbind(rmvnorm(40, mean=c(0,1),sigma = 0.05*diag(2)),rmvnorm(40, mean=c(0.5,0),sigma = 0.05*diag(2)),rmvnorm(40, mean=c(1,1),sigma = 0.05*diag(2)))

par(mfrow=c(3,2))

colnames(x) = c("x1", "x2")

kmeans.benoit(x, centers = matrix(c(0.5,1,0.5,0,1,1),byrow=T,ncol=2))

dev.off()

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kmeans-clustering.R

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