A decision tree is a model that uses a tree-like graph for finding outcome decisions with probabilities. Decision tree learning is a supervised classification learning.
Its a popular tool in machine learning.
A typical decision tree looks like below
In above figure, 0 and 1 at leaf nodes represent outcome variable classes.Its a binary classification.Names in bold like smoke are predictor variables.Smoke=0 means if smoke=0,then go right else left.Splits are made in all predictor variables in the same way.
If you want to learn about how to implement decision tree in R.Then please follow video tutorial.