- A decision tree consists of nodes and leaves,
with each leaf denoting a class.
- Classes (tall or short) are the outputs of the tree.
- Attributes (gender and height) are a set of features that
describe the data.
- The input data consists of values of the different attributes.
Using these attribute values, the decision tree generates a class
as the output for each input data.
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