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Decision trees: Gini, entropy and splits

Decision trees: 20 questions for classification

A decision tree is the most interpretable ML model. It asks a sequence of binary questions: “age > 30? → yes: go here, no: go there.” At the end of the path — a prediction. You can show it to a doctor, lawyer, or client — they’ll get it. But that’s also the weakness: without constraints, the tree memorizes every training example and fails to generalize.

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