https://github.com/fpsom/IntroToMachineLearning/blob/gh-pages/episodes/04-supervised-learning.md

use the rpart and the rpart.plot package in order to produce and visualize a decision tree

library(rpart)
library(rpart.plot)
myFormula <- Diagnosis ~ Radius.Mean + Area.Mean + Texture.SE

breastCancerData.model <- rpart(myFormula,
                                method = "class",
                                data = breastCancerData.train,
                                minsplit = 10,
                                minbucket = 1,
                                maxdepth = 3,
                                cp = -1)

print(breastCancerData.model$cptable)
rpart.plot(breastCancerData.model)