Creating your first decision tree

Inside rpart, there is therpart() function to build your first decision tree. The function takes multiple arguments:

formula: specifying variable of interest, and the variables used for prediction (e.g. formula = Survived ~ Sex + Age).
data: The data set to build the decision tree (here train).
method: Type of prediction you want. We want to predict a categorical variable, so classification: method = "class".

Your call could look like this:

my_tree <- rpart(Survived ~ Sex + Age,
                 data = train,
                 method ="class")

To visualize the resulting tree, you can use the plot(my_tree) and text(my_tree). The resutling graphs will not be that informative, but R has packages to make it all fancier: rattle, rpart.plot, and RColorBrewer.

Build a decision tree my_tree_two:
You want to predict Survived based on Pclass, Sex, Age, SibSp, Parch, Fare and Embarked.
Use the train data to build the tree
Use method to specify that you want to classify.
Visualize my_tree_two with plot() and text().
Load the R packages rattle, rpart.plot, and RColorBrewer.
Use fancyRpartPlot(my_tree) to create a much fancier visualization of your tree.

Exercise

Creating your first decision tree

Instructions