Use this tag for questions about graphs or models of decisions and their possible consequences including chance-event outcomes, resource costs, and utility.
A decision tree is a flowchart-like structure in which each internal node represents a "test" on an attribute (e.g. whether a coin flip comes up heads or tails), each branch represents the outcome of the test and each leaf node represents a class label (decision taken after computing all attributes). The paths from root to leaf represents classification rules.
A decision tree consists of $3$ types of nodes:
- Decision nodes - represented by squares ($\square$)
- Chance nodes - represented by circles ($\circ$)
- End nodes - represented by triangles ($\triangle$)
