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- sdata = read.csv('sdata.txt')
- library(cluster)
- X = c(-4, 0, 4)
- Y = c(10, 0, 10)
- rnames = c("x1", "x2", "x3")
- centers = data.frame(X, Y, row.names = rnames)
- model = kmeans(sdata, centers = centers)
- # model$centers
- # model$cluster
- # Calculate cohesion and separation
- cohesion = model$tot.withinss
- separation = model$betweenss
- # Q1
- cohesion
- # Q2
- separation
- # Plot the data with the clusters
- plot(sdata, col = model$cluster)
- points(model$centers, col = 4, pch = "+", cex = 2)
- # Calculate and plot silhouette
- model_silhouette = silhouette(model$cluster, dist(sdata))
- plot(model_silhouette)
- mean_silhouette = mean(model_silhouette[, 3])
- # Q3
- mean_silhouette
- X= c(-2, 2, 0)
- Y = c(0, 0, 10)
- rnames = c("x1", "x2", "x3")
- centers = data.frame(X, Y, row.names = rnames)
- model = kmeans(sdata, centers = centers)
- model$centers
- model$cluster
- # Plot the data with the clusters
- plot(sdata, col = model$cluster)
- points(model$centers, col = 4, pch = "+", cex = 2)
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