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Lazy learning vs. eager learning

Lazy learning vs. eager learning. Processing is delayed until a new instance must be classified Pros: Classification hypothesis is developed locally for each instance to be classified Cons: Running time (no model is built, so each classification actually builds a local model from scratch).

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