Hierarchical Clustering Iris

gistfile1.txt

library(dplyr)
library(ggplot2)

setwd('D:\\ToyData')

OrginalData <- read.table("IrisData.txt",
                   header = TRUE, sep = "\t")

SubsetData <- subset(OrginalData, select = c(
#"SepalLength"
#,"SepalWidth"
,"PetalLength"
,"PetalWidth"
))

clusters = hclust(dist(SubsetData), method = 'average')
plot(clusters)

clusterCut <- cutree(clusters, 3)
table(clusterCut, OrginalData$Species)
			
ggplot(OrginalData, aes(PetalLength, PetalWidth, color = OrginalData$Species)) + 
  geom_point(alpha = 0.4, size = 3.5) + geom_point(col = clusterCut) + 
  scale_color_manual(values = c('black', 'red', 'green'))