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Leaf node

As explained in Statistics Slam Dunk

A terminal node is an endpoint of a decision tree at which a final prediction is assigned and no further split occurs.

A leaf node, or terminal node, is an endpoint at the bottom of a regression tree. It receives the final prediction, and no further split follows. section 5.8

Regression-tree predictions

A regression tree for regular-season NBA wins contains 10 leaves. Each leaf represents a final predicted win value or range after conditions such as screen assists and deflections have been applied. section 5.8

How Statistics Slam Dunk covers it

How deep it goes
Defines leaves as tree endpoints and connects them to splits, but stops short of explaining their internal fitting mechanics.
Examples
Uses an NBA regression tree with 10 leaves predicting regular-season wins from screen assists, deflections, and other predictors.
What you can do after
Evaluate/understand final regression-tree predictions by reading leaf endpoints and the conditions that lead to them.
How it connects
Connects leaf nodes to regression trees, predictors, splits, and if-else rules.

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Related concepts

This explainer was generated by Manning's knowledge graph from the text of Statistics Slam Dunk. The section links point to the parts of the book it draws on.