machine-learning-with-R/Decision Tree Regression at master · sudheera96/machine-learning-with-R · GitHub

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plot(Position_Salaries)
Position_Salaries<-Position_Salaries[2:3]

#fitting the Decision tree regression
library(rpart)
regressor=rpart(formula = Salary~.,data = Position_Salaries,control = rpart.control(minsplit = 1))

#predict
y_predict=predict(regressor,data.frame(Level=6.5))


#plotting the decision tree
library(ggplot2)
ggplot()+
  geom_point(aes(x=Position_Salaries$Level,y=Position_Salaries$Salary),color='red')+
  geom_line(aes(x=Position_Salaries$Level,y=predict(regressor,newdata = Position_Salaries)),color='blue')+
  ggtitle('truth or bluff(decision tree regression)')+
  xlab('level')+
  ylab('salary')

#plotting the decision tree with high resolution
library(ggplot2)
x_grid=seq(min(Position_Salaries$Level),max(Position_Salaries$Level),0.1)
ggplot()+
  geom_point(aes(x=Position_Salaries$Level,y=Position_Salaries$Salary),color='red')+
  geom_line(aes(x=Position_Salaries$Level,y=predict(regressor,newdata = Position_Salaries)),color='blue')+
  ggtitle('truth or bluff(decision tree regression)')+
  xlab('level')+
  ylab('salary')