d <- read.csv(‘https://stats.dip.jp/01_ds/data/iris.csv’)

library(DT) datatable(d, options = list(pagelength = 5))

library(rpart) library(rpart.plot) tree <- rpart(Species ~ Sepal.Length+Sepal.Width+Petal.Length+Petal.Width, data = d, method = ‘class’, cp = 0.02)

rpart.plot(tree, branch.type = 5) plotcp(tree)

tree2 <- prune(tree, cp = 0.1)

rpart.plot(tree2, branch.type = 5)

tree3 <- prune(tree, cp = 0.02)

rpart.plot(tree3, branch.type = 5)

rpart.predict(tree, rules = T, newdata = data.frame(Sepal.Length = 4.0, Sepal.Width = 3.0, Petal.Length = 3.0, Petal.Width = 1.0 ))