Partitioning Overview
Variations of partitioning go by many names and brand names: decision trees, CARTTM, CHAIDTM, C4.5, C5, and others. The technique is often taught as a data mining technique for the following reasons:
it is useful for exploring relationships without having a good prior model
it handles large problems easily
the results are very interpretable
A classic application is where you want to turn a data table of symptoms and diagnoses of a certain illness into a hierarchy of questions. These questions help diagnose new patients more quickly.
The factor columns (Xs) can be either continuous or categorical (nominal or ordinal). If an X is continuous, then the splits (partitions) are created by a cutting value. The sample is ...

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