Introduction to Decision Trees
Get introduced to decision trees.
The uses of decision tree models are given below:
They are used for both classification and regression (CART).
They answer sequential questions and send us down a specific tree route to find the outcomes class.
They behave like “if this, then that” conditions ultimately yield a particular result.
Context
Let’s say someone wants to practice soccer. Before they decide to go out, they have a few questions about the weather.
Decisions Table
Outlook | Windy | Humidity | Playing |
Sunny | T | High | No |
Overcast | T | Normal | Yes |
Rainy | T | Normal | Yes |
Rainy | T | High | No |
Sunny | F | Normal | Yes |
. | . | . | . |
. | . | . | . |
. | . | . | . |
As the decision table goes on, we can visualize whether or not to play based on the weather.
The decision tree above has the following features:
Root node: The starting point of the tree—for example, "Outlook".
Branches: Arrow lines connecting nodes, showing the flow from question to answer segments of the trees that connect the nodes.
Leaf node: ...