Decision trees are supervised models that can either preform regression or classification.
Let's take a look at some major league baseball player data from 1986-1987. Each dot represents a single player in the league:
- Years (x axis): Number of years played in the major leagues
- Hits (y axis): Number of hits the player had in the previous year
- Salary (color): Low salary is blue/green, high salary is red/yellow
The preceding data is our training data. The idea is to build a model that predicts the salary of future players based on Years and Hits. A decision tree aims to make splits on our data in order to segment the data points that act ...